Journal articles: 'Medical Machines'

1

Hosseini, *. Syed Abbas. "Estimation Risk of X-Ray Machines From Medical Procedures." International Journal of Scientific Research 3, no. 2 (June 1, 2012): 418–19. http://dx.doi.org/10.15373/22778179/feb2014/137.

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Wartman, Steven A. "Medicine, Machines, and Medical Education." Academic Medicine 96, no. 7 (March 30, 2021): 947–50. http://dx.doi.org/10.1097/acm.0000000000004113.

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MANABE, H. "Consideration of Medical-Machines Central Managenent." JAPANES JOURNAL OF MEDICAL INSTRUMENTATION 60, no. 3 (March 1, 1990): 121–28. http://dx.doi.org/10.4286/ikakikaigaku.60.3_121.

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Holzman, Robert S. "Anesthesia Machines." AORN Journal 52, no. 1 (July 1990): 69–76. http://dx.doi.org/10.1016/s0001-2092(07)67286-x.

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Miller, D. Douglas, and Eric W. Brown. "How Cognitive Machines Can Augment Medical Imaging." American Journal of Roentgenology 212, no. 1 (January 2019): 9–14. http://dx.doi.org/10.2214/ajr.18.19914.

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Scislo, Lukasz, and Nina Szczepanik-Scislo. "Influence of mechanical ventilation and cooling systems on vibrations of high precision machines." E3S Web of Conferences 100 (2019): 00080. http://dx.doi.org/10.1051/e3sconf/201910000080.

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The aim of the research was to describe the effects that air and water cooling systems can have on the dynamic behaviour of precise machines. Although much thought is paid to vibration isolation of the ground and isolation of individual effects of machines operating close to each other, it is often forgotten to model or to measure the effects that the ventilation or the machines cooling systems have on the machine itself. This can be especially important for high precision machines used for experimental research and medical equipment. The article shows the effects of ventilation and cooling system on the induction of additional resonant frequencies of the system for the high precision machine like a linear collider. This kind of machine requires special environmental conditions to assure proper beam stability. Due to the dynamic behaviour of typical machines, the presence of the new high amplitude frequencies in the 0-100 Hz range is very dangerous for its stability of work. In the case of high precision machines, it is not only a cause of not optimal working conditions but very often is a cause of serious problems.

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SAKAMOTO, RYOSUKE. "Respondence of medical machines for open heart surgery." Japanese journal of extra-corporeal technology 17, no. 1 (1991): 39–42. http://dx.doi.org/10.7130/hokkaidoshakai.17.39.

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Bentaouza, Chahinez Meriem, and Mohamed Benyettou. "Support Vector Machines for Microscopic Medical Images Compression." Pakistan Journal of Biological Sciences 17, no. 3 (February 15, 2014): 335–45. http://dx.doi.org/10.3923/pjbs.2014.335.345.

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Ellaway, Rachel H. "Medical education and the war with the machines." Medical Teacher 36, no. 10 (September 12, 2014): 917–18. http://dx.doi.org/10.3109/0142159x.2014.955088.

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Basoglu, Chris, Ravi Managuli, George York, and Yongmin Kim. "Computing requirements of modern medical diagnostic ultrasound machines." Parallel Computing 24, no. 9-10 (September 1998): 1407–31. http://dx.doi.org/10.1016/s0167-8191(98)00064-7.

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Takeuchi, Koichi, and Nigel Collier. "Bio-medical entity extraction using support vector machines." Artificial Intelligence in Medicine 33, no. 2 (February 2005): 125–37. http://dx.doi.org/10.1016/j.artmed.2004.07.019.

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Bernards, A. T., H. I. J. Harinck, L. Dijkshoorn, T. J. K. van der Reijden, and P. J. van den Broek. "Persistent Acinetobacter baumannii? Look Inside Your Medical Equipment." Infection Control & Hospital Epidemiology 25, no. 11 (November 2004): 1002–4. http://dx.doi.org/10.1086/502335.

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AbstractTwo outbreaks of multidrug-resistant Acinetobacter baumannii occurred in our hospital. The outbreak strains were eventually isolated from respiratory ventilators, an apparatus used to cool or warm patients, and four continuous veno-venous hemofiltration machines. Removing dust from the machines and replacing all dust filters brought the outbreaks to an end.

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Remarchuk, M., O. Kebko, and O. Halytsky. "THEORETICAL SUBSTANTIATION OF THE EFFICIENCY OF MACHINES FOR EARTH WORKS BASED ON THEIR TECHNICAL PARAMETERS." Municipal economy of cities 4, no. 171 (October 17, 2022): 18–24. http://dx.doi.org/10.33042/2522-1809-2022-4-171-18-24.

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The characteristic features of modern MZRs are that they are divided into cyclic and continuous machines, which depends on their productivity and power of internal combustion engines, and the design of their working equipment affects the process of specific application of MZRs for the construction of appropriate earthworks with different labor intensity. When using MZR, the main question arises about the effectiveness of their functioning from the point of view of knowing the actual state, the amount of fuel consumption required to perform a given volume of work and inefficient fuel losses. The purpose of the article is to determine the real state for known MZR based on the use of reference parameters and to ensure the given state at the design stage of such machines based on the application of system analysis with the establishment of numerical indicators that are characterized by objectivity, ambiguity and accuracy of their determination. The conducted studies are based on the application of system analysis when considering MZR using their reference technical and economic parameters, as a complex system with structural elements functionally interconnected and capable of transmitting hydraulic and mechanical energy. Moreover, MZR is studied as a system that is suitable for converting input power into useful work at the output and, on this basis, is able to determine its internal state due to the overall efficiency and the amount of specific fuel consumption. Based on the results of the research, it was found that the most effective MZR are machines with a continuous working process and they are characterized by high values of the total efficiency of the machine at the level of (8 to 14)%, and gradually the total efficiency decreases to several tenths of a percent for machines of cyclic action. Research has established that in each of the ten MZR groups there is a machine that has the highest total efficiency, and the value of specific fuel consumption per unit of productivity for it is the smallest, and such a machine is classified as exemplary. Other MZR from this group with a low value of total efficiency and higher specific fuel consumption are classified as ordinary cars. According to the conducted studies, it is possible to ensure the selection of the best MZR to create a squad of machines from them, directed to perform a specific volume of work with minimal fuel loss. The internal state of MZR by the value of the total efficiency can be diagnosed at the stage of completion of production, as well as during operation due to the measurement of input and output parameters based on the use of modern means for recording these parameters. Keywords: earthmoving machines, power, fuel, efficiency.

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Emonts, Caroline, Niels Grigat, Felix Merkord, Ben Vollbrecht, Akram Idrissi, Johannes Sackmann, and Thomas Gries. "Innovation in 3D Braiding Technology and Its Applications." Textiles 1, no. 2 (July 7, 2021): 185–205. http://dx.doi.org/10.3390/textiles1020009.

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Braids are generally divided into 2D braids and 3D braids. Two-dimensional braids include flat braids and circular braids. Circular braids represent three-dimensional textiles, as they enclose a volume, but consist of a two-dimensional yarn architecture. Three-dimensional braids are defined by a three-dimensional yarn architecture. Historically, 3D braids were produced on row and column braiding machines with Cartesian or radial machine beds, by bobbin movements around inlay yarns. Three-dimensional rotary braiding machines allow a more flexible braiding process, as the bobbins are moved via individually controlled horn gears and switches. Both braiding machines at the Institut für Textiltechnik (ITA) of RWTH Aachen University, Germany, are based on the principal of 3D rotary machines. The fully digitized 3D braiding machine with an Industry 4.0 standard enables the near-net-shape production of three-dimensionally braided textile preforms for lightweight applications. The preforms can be specifically reinforced in all three spatial directions according to the application. Complex 3D structures can be produced in just one process step due to the high degree of design freedom. The 3D hexagonal braiding technology is used in the field of medical textiles. The special shape of the horn gears and their hexagonal arrangement provides the densest packing of the bobbins on the machine bed. In addition, the lace braiding mechanism allows two bobbins to occupy the position between two horn gears, maximizing the number of bobbins. One of the main applications is the near-net-shape production of tubular structures, such as complex stent structures. Three-dimensional braiding offers many advantages compared to 2D braiding, e.g., production of complex three-dimensional geometries in one process step, connection of braided layers, production of cross-section changes and ramifications, and local reinforcement of technical textiles without additional process steps. In the following review, the latest developments in 3D braiding, the machine development of 3D braiding machines, as well as software and simulation developments are presented. In addition, various applications in the fields of lightweight construction and medical textiles are introduced.

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L. Melgoza, Evila, Guillem Vallicrosa, Lidia Serenó, Joaquim Ciurana, and Ciro A. Rodríguez. "Rapid tooling using 3D printing system for manufacturing of customized tracheal stent." Rapid Prototyping Journal 20, no. 1 (January 14, 2014): 2–12. http://dx.doi.org/10.1108/rpj-01-2012-0003.

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Purpose – This work aims to present the design of a new continuous tool-path strategy for open-source low-cost fused deposition modeling (FDM) machines, such as Fab@Home or RepRap; and the development of an innovative integrated tool to design and fabricate customized tracheal stents with any FDM machine and six patient parameters. Both contributions were validated and implemented by obtaining a customized medical-grade silicone tracheal stent. Design/methodology/approach – For the design of the new deposition strategy, a Python programming language was used. The new tool-path strategy was proposed as a continuous path to avoid drops and gaps and to improve the accuracy of the final model. Meanwhile, patient parameters were obtained by medical doctors and introduced into the innovative integrated system. On the one hand, one mold generated automatically, and viewed with Matlab® software, was fabricated with a Fab@Home machine, optimized with the continuous tool-path strategy. On the other hand, the same generated mold was viewed in SolidWorks/Excel software and was fabricated using a commercial FDM machine. Finally, the mold was filled with medical grade silicone, and a silicone tracheal stent was obtained. Findings – Path planning for extrusion technologies is still a major concern, especially for open-source FDM machines. The results obtained in this work show the benefits of applying the newly developed continuous tool-path strategy to optimize the performance and efficiency of these machines. In addition, the proposed innovative integrated system allows the fabrication of customized tracheal stents rapidly and affordably. Practical implications – The possibility of obtaining customized tracheal stents is a worthy challenge. Medical doctors could play a more active role and interact during the design process, helping to obtain more suitable stents. The method proposed herein would provide the opportunity to obtain real values from the trachea of a patient in the operating room and quickly fabricate a customized stent that would fit the patient's trachea perfectly. Originality/value – The results obtained in this work are relevant and have future applications in both the medical and the additive manufacturing fields. The optimized tool-path strategy can help to improve and enhance the use of low-cost FDM machines. Moreover, the innovative automatic design approach to fabricate tracheal stents may open new market opportunities in the medical device field.

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Zinn, Marc-Kevin, Hans-Curt Flemming, and Dirk Bockmühl. "A Comprehensive View of Microbial Communities in the Laundering Cycle Suggests a Preventive Effect of Soil Bacteria on Malodour Formation." Microorganisms 10, no. 7 (July 20, 2022): 1465. http://dx.doi.org/10.3390/microorganisms10071465.

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Microorganisms are an important factor in the wash-and-use cycle of textiles since they can cause unwanted aesthetic effects, such as malodour formation, and even pose health risks. In this regard, a comprehensive view of the microbial communities in washing machines and consideration of the microbial contamination of used textiles is needed to understand the formation of malodour and evaluate the infection risk related to laundering. So far, neither the compositions of washing machine biofilms leading to the formation of or protection against malodour have been investigated intensively, nor have microbial communities on used towels been analysed after normal use. Our results link the qualitative and quantitative analysis of microbial communities in washing machines and on used towels with the occurrence of malodour and thus not only allow for a better risk evaluation but also suggest bacterial colonizers of washing machines that might prevent malodour formation. It was shown that soil bacteria such as Rhizobium, Agrobacterium, Bosea, and Microbacterium in particular are found in non-odourous machines, and that Rhizobium species are able to prevent malodour formation in an in vitro model.

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Song, Eun-Sung, Young-Jun Lim, Joongsoo Lee, Jung-Bon Moon, and Bongju Kim. "Application of Soundproofing Materials for Noise Reduction in Dental CAD/CAM Milling Machines." Applied Sciences 10, no. 8 (April 16, 2020): 2768. http://dx.doi.org/10.3390/app10082768.

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Soundproofing materials are widely used in various fields as a passive measure to reduce noise. Despite this, there have been a few studies on the application of soundproofing materials on medical equipment, which is the main cause of noise in a medical environment. Despite the increasing number of studies on active noise control for the noise reduction of machines, it is difficult to apply customized noise control—i.e., specific control measures according to the various characteristics of that noise—due to its high cost and low effectiveness. Therefore, research on passive noise control using soundproofing materials is required for effective noise control. The 3D CAD/CAM milling machine, which is an essential device in the digitalized dental environment, is causing various problems as a new noise source. This study investigated the noise of the milling machine and considered its characteristics in application of an efficient soundproofing material for noise reduction. Additionally, a soundproofing material performance test was conducted to select an appropriate soundproofing material based on the noise characteristics of the milling machine. As milling machines cause noise issues in hospitals, the study results were analyzed in considering practical aspects for immediate application to actual sale products. This study suggests that the application of Thinsulator and a triple soundproofing mat (butyl 100% + aluminum + sound-insulating material) is effective in the noise reduction of milling machines.

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Iqeilan, Nabil, Antar Aly, Salha Al Mohannadi, and Huda Al Naemi. "Quality Control Program in Medical Ultrasound at Hamad Medical Corporation: Current Status." European Journal of Medical and Health Sciences 4, no. 2 (March 11, 2022): 23–26. http://dx.doi.org/10.24018/ejmed.2022.4.2.995.

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The main purpose of QC program in diagnostic imaging modalities such as medical ultrasound equipment is to evaluate and define the performance and safety of ultrasound equipment. Ultrasound systems contain many sensitive transducers and soft parts which may be destroyed due to poor handling or use. Over time, any machines, regardless of their quality and usage, depreciates and incurs damage in many ways. The results from the Quality Control (QC) reports for B-mode of the Ultrasound machines in the Clinical Imaging Department of Hamad Medical Corporation (HMC) has been reviewed. The average annual failures of equipment during the 4-year period includes 2.7% involved transducers and 51.3% involved mechanical integrity failures while the average annual failures rate from mechanical integrity and transducers were measured to be 12.8% and 0.7%, respectively. The main failure of the transducers could be from some artifacts or bad connection of individual elements or groups of elements. Evaluation of maximum depth of penetration showed that the measurement of distance accuracy is not effective in detecting equipment failures [1].

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Janardhanan, Padmavathi, Heena L., and Fathima Sabika. "Effectiveness of Support Vector Machines in Medical Data mining." Journal of Communications Software and Systems 11, no. 1 (March 23, 2015): 25. http://dx.doi.org/10.24138/jcomss.v11i1.114.

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The idea of medical data mining is to extract hidden knowledge in medical field using data mining techniques. One of the positive aspects is to discover the important patterns. It is possible to identify patterns even if we do not have fully understood the casual mechanisms behind those patterns. In this case, data mining prepares the ability of research and discovery that may not have been evident. This paper analyzes the effectiveness of SVM, the most popular classification techniques in classifying medical datasets. This paper analyses the performance of the Naïve Bayes classifier, RBF network and SVM Classifier. The performance of predictive model is analysed with different medical datasets in predicting diseases is recorded and compared. The datasets were of binary class and each dataset had different number of attributes. The datasets include heart datasets, cancer and diabetes datasets. It is observed that SVM classifier produces better percentage of accuracy in classification. The work has been implemented in WEKA environment and obtained results show that SVM is the most robust and effective classifier for medical data sets.

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Schneider, F. K., A. Agarwal, Yang Mo Yoo, T. Fukuoka, and Yongmin Kim. "A Fully Programmable Computing Architecture for Medical Ultrasound Machines." IEEE Transactions on Information Technology in Biomedicine 14, no. 2 (March 2010): 538–40. http://dx.doi.org/10.1109/titb.2009.2025653.

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Zanetti, François. "Curing with Machines: Medical Electricity in Eighteenth-Century Paris." Technology and Culture 54, no. 3 (2013): 503–30. http://dx.doi.org/10.1353/tech.2013.0102.

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Anson, J. J., and K. D. Allen. "Hospital ice machines." Journal of Hospital Infection 37, no. 4 (December 1997): 335–36. http://dx.doi.org/10.1016/s0195-6701(97)90152-3.

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Ayliffe, G. A. J. "Washer/disinfection machines." Journal of Hospital Infection 9, no. 1 (January 1987): 99–100. http://dx.doi.org/10.1016/0195-6701(87)90111-3.

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Gardner, C. A. "Ice-making machines." Journal of Hospital Infection 29, no. 4 (April 1995): 312. http://dx.doi.org/10.1016/0195-6701(95)90280-5.

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Whitehead, Kelly, Jake Eppinger, Vanita Srinivasan, M. Khalid Ijaz, Raymond W. Nims, and Julie McKinney. "Potential for Microbial Cross Contamination of Laundry from Public Washing Machines." Microbiology Research 13, no. 4 (December 9, 2022): 995–1006. http://dx.doi.org/10.3390/microbiolres13040072.

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Although clothes washing machines remove dirt, microorganisms are not reliably removed by modern cold-water machine-washing practices. Microbial bioburden on clothing originates from the wearer’s skin, the environment (indoor and outdoor), and the washing machine itself. While most clothing microbes are commensals, microbes causing odors and opportunistic pathogens may also be present. Understanding the extent of microbial transfer from washing machines to clothes may inform strategies for odor control and for mitigating the transmission of microbes through the laundering process. This study was designed to quantify and identify bacteria/fungi transferred from laundromat machines to sentinel cotton washcloths under standard cold-water conditions. Bacterial 16S rRNA and fungal ITS sequencing enabled identification of microorganisms in the washcloths following laundering. Total plate-based enumeration of viable microorganisms also was performed, using growth media appropriate for bacteria and fungi. Opportunistic human bacterial pathogens, including Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp., were recovered. The fungal bioburden was ~two-fold lower than the bacterial bioburden. Most sequences recovered were assigned to non-pathogenic fungi, such as those from genera Malassezia and Ascomycota. These results suggest that public washing machines represent a source of non-pathogenic and pathogenic microbial contamination of laundered garments.

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Hasan, Waqas. "A Survey on Virtual Machine Migration in Cloud Computing." International Journal of Scientific & Engineering Research 13, no. 03 (March 25, 2022): 648–53. http://dx.doi.org/10.14299/ijser.2022.03.03.

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Cloud computing provides multiple services to users through the internet and these services include cloud storage, applications, servers, security and large network access. Virtual Machine allows the user to emulate multiple operating systems on a single computer; with the help of virtual machine migration users can transfer operating system instances from one computer to multiple computer machines. In this paper we will be discussing VM migration in cloud and also I will explain the whole procedure of VM migration. The two methods through which we can perform VM migration are Live VM migration and NON-live VM migration.VM migration also helps in managing the loads of the multiple machines and with VM we can save power consumption. People have written about cloud computing and virtual machines in previous studies, but in this research, we'll speak about virtual machine migration in cloud computing, as well as the techniques that are used in the VM migration process. I have used table to show the differences between VM migration techniques.

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Salsiani Sinta, Niska, and Wahyu Sulistiawan. "FAKTOR-FAKTOR YANG MENGHAMBAT PELAYANAN PENERIMAAN PASIEN RAWAT JALAN DI RUMAH SAKIT UMUM DAERAH KABUPATEN BUTON." Jurnal Sains dan Kesehatan 1, no. 2 (November 18, 2022): 30–42. http://dx.doi.org/10.57151/jsika.v1i2.46.

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Registration service is one of the most important factors in the activities in the hospital, which is the beginning of the patient getting a good or bad impression of the services provided by all health workers in the hospital. The path consists of Man, Machine, Money, Material, and Method. This research was conducted in the medical record unit for receiving RJ patients at the Buton District Hospital. This type of research uses a descriptive research design with a qualitative study approach. The subjects in this study were patient registration officers, head of medical records and patients. The object of this research is the factors that hinder the service of receiving RJ patients. The data collection methods used were observation and interviews. Based on the results of the study, there were 13 medical record officers with details of 5 officers who graduated from medical records and 8 others including public health graduates. The machines used are still lacking, there are no queuing machines, loudspeakers, network access that is still not running well, and generators that are always damaged so that when a light goes out, the service will be stopped. The allocated funds are still very less. The materials used are sufficient, however, in making KIB it is still done manually. There is no SOP for accepting outpatients.The Man, Machines, Money, Material, Method still hinder the outpatient admission service.

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LIN, Fen. "人工智能批判的話語悖論." International Journal of Chinese & Comparative Philosophy of Medicine 17, no. 2 (January 1, 2019): 133–37. http://dx.doi.org/10.24112/ijccpm.171683.

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LANGUAGE NOTE | Document text in Chinese; abstract in English only.In the dominant discourse of the "human–machine relationship," people and machines are the subjects, with a mutually shaping influence. However, this framework neglects the crux of the current critical analysis of AI. It reduces the problems with new technology to the relationship between people and machines, ignoring the re-shaping of the relationship between "people and people" in the era of new technology. This simplification may mislead policy and legal regulations for new technologies. Why would a robot killing cause more panic than a murder committed by a human? Why is a robot's misdiagnosis more troubling than a doctor's? Why do patients assume that machines make more accurate diagnoses than doctors? When a medical accident occurs, who is responsible for the mistakes of an intelligent medical system? In the framework of traditional professionalism, the relationship between doctors and patients, whether trusted or not, is based on the premise that doctors have specialized knowledge that patients do not possess. Therefore, the authority of a doctor is the authority of knowledge. In the age of intelligence, do machines provide information or knowledge? Can this strengthen or weaken the authority of doctors? It is likely that in the age of intelligence, the professionalism, authority and trustworthiness of doctors require a new knowledge base. Therefore, the de-skilling of doctors is not an issue of individual doctors, but demands an update of the knowledge of the entire industry. Recognizing this, policy makers must not focus solely on the use of machines, but take a wider perspective, considering how to promote the development of doctors and coordinate the relationship between doctors with different levels of knowledge development. We often ask, "In the era of intelligence, what defines a human?" This philosophical thinking should be directed toward not only the difference between machines and people as individuals, but also how the relationship between human beings, i.e., the social nature of humans, evolves in different technological environments. In short, this commentary stresses that a "good" machine or an "evil" machine—beyond the sci-fi romance of such discourse—reflects the evolution of the relationships between people. In today's smart age, the critical issue is not the relationship between people and machines. It is how people adjust their relationships with other people as machines become necessary tools in life. In the era of intelligence, therefore, our legislation, policy and ethical discussion should resume their focus on evolutionary relationships between people.DOWNLOAD HISTORY | This article has been downloaded 41 times in Digital Commons before migrating into this platform.

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Whittum, David H. "Microwave Electron Linacs for Oncology." Reviews of Accelerator Science and Technology 02, no. 01 (January 2009): 63–92. http://dx.doi.org/10.1142/s1793626809000260.

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The history and technology of medical linacs are reviewed, focusing on machine requirements for radiotherapy. Configurations used in modern machines are described and operational aspects of a gantry-style linac system are illustrated with reference to the state of the art. Aspects of structure design, modeling and testing are discussed.

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Winkler, Stephan M., Gabriel Kronberger, Michael Affenzeller, and Herbert Stekel. "Variable Interaction Networks in Medical Data." International Journal of Privacy and Health Information Management 1, no. 2 (July 2013): 1–16. http://dx.doi.org/10.4018/ijphim.2013070101.

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In this paper the authors describe the identification of variable interaction networks based on the analysis of medical data. The main goal is to generate mathematical models for medical parameters using other available parameters in this data set. For each variable the authors identify those features that are most relevant for modeling it; the relevance of a variable can in this context be defined via the frequency of its occurrence in models identified by evolutionary machine learning methods or via the decrease in modeling quality after removing it from the data set. Several data based modeling approaches implemented in HeuristicLab have been applied for identifying estimators for selected continuous as well as discrete medical variables and cancer diagnoses: Genetic programming, linear regression, k-nearest-neighbor regression, support vector machines (optimized using evolutionary algorithms), and random forests. In the empirical section of this paper the authors describe interaction networks identified for a medical data base storing data of more than 600 patients. The authors see that whatever modeling approach is used, it is possible to identify the most important influence factors and display those in interaction networks which can be interpreted without domain knowledge in machine learning or informatics in general.

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Logan, Mary, Carol Davis-Smith, and Alan Gresch. "Maintenance and repair of anesthesia machines." AORN Journal 93, no. 2 (February 2011): 195. http://dx.doi.org/10.1016/j.aorn.2010.12.008.

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Spalanzani, Widya, Salwiah, and Asmuddin. "Pengaruh Metode Campbell Dudeck Smith dalam Penjadwalan Produksi Table 76-0001-Veneer Mesin Shop PT. Cegeone." Jurnal Jaring SainTek 3, no. 2 (October 31, 2021): 38–44. http://dx.doi.org/10.31599/jaringsaintek.v3i2.694.

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CEGEONE (CG) is a manufacturing industry company in furniture. It is a supplier company for the Horrison & Gil company. The company manufactures furniture from raw materials into semi-finished goods. The company produces its products on consumer demand (customized order). The overwhelming and varying amount of demand each period was a major problem in the company's production. Hence it takes scheduling. Production scheduling is an important process in production system. In the production process, particularly in the Shop Machine line there is often bottle neck. Under that, researchers did production scheduling at the Shop Machine with the Campbell Dudeck Smith (CDS) method. This method uses Johnson's algorithm that aims to determine the order of the job in order for the earned makespan to be smaller than before. Using production scheduling on shop machines, the company can reduce the total process time to complete the job by 95 minutes or 1 hour 35 minutes. Smaller compared to the previous total makespan of 250 minutes or 4 hours 10 minutes. So that shows total savings in production at 19.79%. The results of the study can be concluded that by using production scheduling on shop machines.

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Pugliese, Gina, and Martin S. Favero. "Maintenance of Ice Machines." Infection Control & Hospital Epidemiology 20, no. 6 (June 1999): 420. http://dx.doi.org/10.1017/s0195941700070478.

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Steil, Jochen, Dominique Finas, Susanne Beck, Arne Manzeschke, and Reinhold Haux. "Robotic Systems in Operating Theaters: New Forms of Team–Machine Interaction in Health Care." Methods of Information in Medicine 58, S 01 (June 2019): e14-e25. http://dx.doi.org/10.1055/s-0039-1692465.

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Background Health information systems have developed rapidly and considerably during the last decades, taking advantage of many new technologies. Robots used in operating theaters represent an exceptional example of this trend. Yet, the more these systems are designed to act autonomously and intelligently, the more complex and ethical questions arise about serious implications of how future hybrid clinical team–machine interactions ought to be envisioned, in situations where actions and their decision-making are continuously shared between humans and machines. Objectives To discuss the many different viewpoints—from surgery, robotics, medical informatics, law, and ethics—that the challenges of novel team–machine interactions raise, together with potential consequences for health information systems, in particular on how to adequately consider what hybrid actions can be specified, and in which sense these do imply a sharing of autonomous decisions between (teams of) humans and machines, with robotic systems in operating theaters as an example. Results Team–machine interaction and hybrid action of humans and intelligent machines, as is now becoming feasible, will lead to fundamental changes in a wide range of applications, not only in the context of robotic systems in surgical operating theaters. Collaboration of surgical teams in operating theaters as well as the roles, competencies, and responsibilities of humans (health care professionals) and machines (robotic systems) need to be reconsidered. Hospital information systems will in future not only have humans as users, but also provide the ground for actions of intelligent machines. Conclusions The expected significant changes in the relationship of humans and machines can only be appropriately analyzed and considered by inter- and multidisciplinary collaboration. Fundamentally new approaches are needed to construct the reasonable concepts surrounding hybrid action that will take into account the ascription of responsibility to the radically different types of human versus nonhuman intelligent agents involved.

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Chen, Hsin Hua, Ping Feng Pai, Ying Zhieh Cho, Fong Chuan Lee, and Ja Chih Fu. "An improved support vector machines model in medical data analysis." International Journal of Mathematical Modelling and Numerical Optimisation 1, no. 3 (2010): 168. http://dx.doi.org/10.1504/ijmmno.2010.031747.

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Valenti, Michael. "Making the Cut." Mechanical Engineering 123, no. 11 (November 1, 2001): 64–67. http://dx.doi.org/10.1115/1.2001-nov-4.

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This article discusses the electrochemical machining (ECM), a noncontact technology that spares both tool and part from machining wear, and the ECM finishes some parts in half the time of conventional mechanical machining techniques. The Sermatech Manufacturing Group, a leading user of ECM, is researching new applications for the technology, which the company uses principally on turbine components and various aircraft parts. In the ECM process, the DC power source charges the workpiece positively and charges the tool negatively. As the machine slowly brings the tool and workpiece close together, perhaps to within 0.010 of an inch, the power and electrolyte flow are turned ON. Everite engineers developed a thinner cutting wheel version of its ECG machines to cut fine stainless steel tubing for medical devices without burrs. Other tiny medical devices made by Everite machines include biopsy needles, nickel titanium threading catheters, and cobalt–chrome alloy joint implants.

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Cazals, Margot, Emilie Bedard, Michele Provost, and Patrice Savard. "Is your ice machine really clean? Uncovering the presence of opportunistic pathogens in hospital ice machines." Antimicrobial Stewardship & Healthcare Epidemiology 2, S1 (May 16, 2022): s12—s13. http://dx.doi.org/10.1017/ash.2022.76.

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Background: Ice is used in healthcare facilities for medical purposes and consumption by the medical staff and the patients, but some studies have revealed significant microbial contamination of ice machines leading to nosocomial outbreaks or pseudooutbreaks and infections by opportunistic pathogens, including the fungi Candida, the bacteria Pseudomonas aeruginosa, and nontuberculous mycobacteria (NTM). Although ice machines are complex devices that are prone to contamination, very little is known about their potential as vectors of infections for populations at risk in hospitals. Only few studies document efficient maintenance regimes, specifically cleaning procedures and microbial indicators that would ensure their safe use. Method: In this prospective study, combined samples of water and ice, and drain biofilm samples were collected from 36 ice and cold-water distribution machines of a recently built hospital, for a total of 72 samples. Physicochemical parameters (total and free chlorine, temperature, etc) were measured in water, and several opportunistic pathogens (ie, Candida spp, P. aeruginosa, NTM) and biological indicators (ie, heterotrophic plate counts (HPCs), total and viable bacteria and enterococci) were monitored in water and ice and biofilm. Culture methods were used for HPCs, Candida spp, P. aeruginosa, and enterococci, and total and viable bacterial populations were estimated using flow cytometry. NTM were monitored by quantitative polymerase chain reaction (qPCR). Results: We observed clear differences between the machines in terms of biological contamination, with frequent detection of NTM and presumed Candida. Thus, NTM were detected in the 36 samples of ice and water with concentrations from 0.5 to 2×104 gene copies/mL. Among the several species of fungi detected in the ice machines, some were identified as C. parapsilosis and C. guilliermondii, which are organisms of concern in healthcare facilities. Factors affecting the level of contamination in ice machines include the location of the machines and water quality (ie, temperature and chlorine residual concentration). Depending on the location in the building and the model of ice machine sampled, the biological indicators measurements indicated more or less significant contamination. No link was established between environmental strains recovered from the machines and clinical infections. Conclusions: Monitoring results showed that ice machines, while subject to few regulations and controls, can be reservoirs of unsuspected opportunistic pathogens that could lead to nosocomial infections of vulnerable patients. Cleaning procedures should be based on the disinfection of resistant opportunistic pathogens, such as Candida and NTM, and the use of general indicators, such as HPCs, should be questioned.Funding: NoneDisclosures: None

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Graman, Paul S., Gail A. Quinlan, and June A. Rank. "Nosocomial Legionellosis Traced to a Contaminated Ice Machine." Infection Control & Hospital Epidemiology 18, no. 09 (September 1997): 637–40. http://dx.doi.org/10.1086/647689.

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Abstract Objective: To investigate a case of nosocomial legionellosis, identify pathways of transmission, and effect control of the environmental source. Design: Case investigation and environmental culture surveillance. Setting: A 720-bed university teaching hospital. Case Patient: A ventilator-dependent 66-year-old male developed nosocomial pneumonia due to Legionella pneumophila serogroup 6 after 3 months in an intensive-care unit (ICU). The patient had no intake of potable water except for ice chips from an ice machine in the ICU. Results: Cultures revealed L pneumophila serogroup 6 in the ice (4.3 colony-forming units/mL) and ice machine cold water (too numerous to count). Cultures from adjacent hot and cold taps, plus taps located near the patient, all were negative; ice machines and cold water on seven other patient units also were negative. Only sterile water had been used for tube feedings, mouth care, suctioning, and ventilator humidification. Hospital hot water previously had been colonized with L pneumophila serogroup 6, but all surveillance water cultures had been negative since chlorination of the hot-water system began the previous year; cold-water cultures had never before grown Legionella. The ice machine was disinfected with a 2-hour flush of 2.625% sodium hypochlorite. The supply line to the ice machine was replaced, and the cold-water pipe from the floor below was treated with 83 ppm sodium hypochlorite for 48 hours. All follow-up surveillance cultures of the ice machine remained negative through mid-1996. No additional cases of nosocomial legionellosis occurred. Conclusions: Ice machines may be reservoirs of L pneumophila in hospitals. Both ice and water dispensed from these machines may be contaminated, and nosocomial transmission may occur. Successful long-term decontamination and control can be accomplished with shock chlorination.

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Et. al., Raswitha Bandi,. "Tensor Flow Model in Medical Image Analysis - Review." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (April 11, 2021): 1389–97. http://dx.doi.org/10.17762/turcomat.v12i5.2032.

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Support Vector Machines, Reinforcement algorithms, artificial neural networks are some of the Machine Learning Algorithms available in Medical Analysis. By using these algorithms, much of the research has been done in analysis of liver cancer for genome classification and identification of lesions. At present, Deep learning algorithms have quickly turned into a strategy for examine CT images. This article presents one of the major deep learning techniques named tensor flow technique to investigate images in scan for the task of visualization of abnormal condition of liver tumor in the context of shape and color towards disease diagnosis. We surveyed the utilization of tensor flow for classifying images, detection of objects, and detection of lesions. In this paper, we mainly concentrated on the study and working of tensor flow in image classification. Also, a summary of the present and future scope in this area has been presented in detail.

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O'brien, H. D. "Vivian Richard Ebsary, A.M. Biomedical Engineer, Inventor, Philanthropist." Anaesthesia and Intensive Care 33, no. 1_suppl (June 2005): 16–20. http://dx.doi.org/10.1177/0310057x0503301s08.

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Vivian Ebsary was an inventor, designer and manufacturer of varied pieces of medical equipment, particularly those involving pumps. These included hypothermia machines and the heart-lung cardiopulmonary bypass machines used in Australian and New Zealand hospitals from the mid 1950s until well into the 1970s. Ebsary also designed and manufactured anaesthetic machines, a hyperbaric unit, scoliosis implant equipment, a chairlift and many other devices for use in the general community. This paper presents an overview of his life's involvement with medicine and medical technology in Australia.

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Peletiri, Iseimokumo Christopher. "Validation of automated malaria parasite diagnostic machines based on first principle: A pre-requisite for acceptable results and treatment monitoring in resource limited settings." Annals of Medical Laboratory Science 2, no. 1 (March 30, 2022): 35–41. http://dx.doi.org/10.51374/annalsmls.2022.2.1.0056.

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Background: Following the very recent introduction of automated malaria parasite diagnostic machines; the need to validate these high technology machines based on the first principle protocol in malaria parasite density determination for acceptable results and treatment monitoring cannot be over-emphasized. The aim of this review is to update Medical Laboratory Scientists, Medical Laboratory Technicians, and researchers alike on the first principle in the diagnosis of malaria using Giemsa stained thick and thin blood films and to build their capacity on how to validate any automated malaria parasite diagnostic machine. Methods: The first principle protocol in malaria parasite density determination was used. With 8 µL of blood spread within 18 mm diameter of circle (thick film), the volume of blood in one thick film field (0.002 µL) is obtained; which when multiplied by a factor (500) gives 1 µL. The number of parasites seen per 100 thick film fields or average number per each thick film field multiplied by 500 gives the number of parasites / µL of blood. Results: Malaria parasites counts of 5 – 50 parasites (1+), 50 – 500 parasites (2+), 500 – 5000 parasites (3+), and (4+) > 5000 parasites / µL of blood, and with the results obtained from the automated machine which when entered into a 2 x 2 table reveal the performance evaluation of automated machine. Conclusion: With several results obtained, any automated malaria diagnostic machine can be validated for its ability to detect disease (sensitivity, specificity, positive and negative predictive values). Commencement of the use of automated malaria parasites diagnostic machines in parasitology laboratory should not lead to discontinuity in the use of thick and thin blood films in malaria diagnosis as it remains the gold standard in resource limited settings.

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Pham, Thang, Patrick Kwon, and Shanelle Foster. "Additive Manufacturing and Topology Optimization of Magnetic Materials for Electrical Machines—A Review." Energies 14, no. 2 (January 6, 2021): 283. http://dx.doi.org/10.3390/en14020283.

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Additive manufacturing has many advantages over traditional manufacturing methods and has been increasingly used in medical, aerospace, and automotive applications. The flexibility of additive manufacturing technologies to fabricate complex geometries from copper, polymer, and ferrous materials presents unique opportunities for new design concepts and improved machine power density without significantly increasing production and prototyping cost. Topology optimization investigates the optimal distribution of single or multiple materials within a defined design space, and can lead to unique geometries not realizable with conventional optimization techniques. As an enabling technology, additive manufacturing provides an opportunity for machine designers to overcome the current manufacturing limitation that inhibit adoption of topology optimization. Successful integration of additive manufacturing and topology optimization for fabricating magnetic components for electrical machines can enable new tools for electrical machine designers. This article presents a comprehensive review of the latest achievements in the application of additive manufacturing, topology optimization, and their integration for electrical machines and their magnetic components.

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Michailidis, Panagiotis, Athanasia Dimitriadou, Theophilos Papadimitriou, and Periklis Gogas. "Forecasting Hospital Readmissions with Machine Learning." Healthcare 10, no. 6 (May 25, 2022): 981. http://dx.doi.org/10.3390/healthcare10060981.

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Hospital readmissions are regarded as a compounding economic factor for healthcare systems. In fact, the readmission rate is used in many countries as an indicator of the quality of services provided by a health institution. The ability to forecast patients’ readmissions allows for timely intervention and better post-discharge strategies, preventing future life-threatening events, and reducing medical costs to either the patient or the healthcare system. In this paper, four machine learning models are used to forecast readmissions: support vector machines with a linear kernel, support vector machines with an RBF kernel, balanced random forests, and weighted random forests. The dataset consists of 11,172 actual records of hospitalizations obtained from the General Hospital of Komotini “Sismanogleio” with a total of 24 independent variables. Each record is composed of administrative, medical-clinical, and operational variables. The experimental results indicate that the balanced random forest model outperforms the competition, reaching a sensitivity of 0.70 and an AUC value of 0.78.

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Kirengo, Thomas Onyango. "Frugal digitization of analog video endoscopic medical records in a Kenyan rural medical center." Annals of African Surgery 20, no. 1 (January 18, 2023): 3–6. http://dx.doi.org/10.4314/aas.v20i1.2.

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Background: Digitization of healthcare data has led to widespread healthcare transformation. This has been enhanced by the availability of new technologies at lower costs. Video recording can improve the quality of care, provider skills, education, and patient follow-up. However, limitations such as the risk of litigation, patient privacy, and poor legal framework have curtailed adoption. Rural hospitals have older analog equipment due to limited financial resources. Objectives: This study aims to present an alternative low-cost option. Methods: We present an economical method of recording and digitizing endoscopic and laparoscopic procedures performed on analog video processing towers. We showcase a video of the step-by-step procedure that involves connecting a digital video home system (VHS) video recorder to an analog Olympus endoscopy machine (Model CV-100) and transferring media via a portable storage device to an electronic medical record database. Conclusion: Using simple home video recording devices provides a low-cost solution to creating digital records from analog video endoscopic machines. The technique, however, creates additional steps to the endoscopy process and the need for capacity building of the endoscopist. Patient consent forms should cover video creation. Medical centers should have a robust information management system to securely store and retrieve digitized video records.

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Ramezanpour, Abolfazl, Andrew L. Beam, Jonathan H. Chen, and Alireza Mashaghi. "Statistical Physics for Medical Diagnostics: Learning, Inference, and Optimization Algorithms." Diagnostics 10, no. 11 (November 19, 2020): 972. http://dx.doi.org/10.3390/diagnostics10110972.

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It is widely believed that cooperation between clinicians and machines may address many of the decisional fragilities intrinsic to current medical practice. However, the realization of this potential will require more precise definitions of disease states as well as their dynamics and interactions. A careful probabilistic examination of symptoms and signs, including the molecular profiles of the relevant biochemical networks, will often be required for building an unbiased and efficient diagnostic approach. Analogous problems have been studied for years by physicists extracting macroscopic states of various physical systems by examining microscopic elements and their interactions. These valuable experiences are now being extended to the medical field. From this perspective, we discuss how recent developments in statistical physics, machine learning and inference algorithms are coming together to improve current medical diagnostic approaches.

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Gupta, Manish, Ihtiram Raza Khan, B. Gomathy, and Ansuman Samal. "Hybrid Multi-User Based Cloud Data Security for Medical Decision Learning Patterns." ECS Transactions 107, no. 1 (April 24, 2022): 2559–73. http://dx.doi.org/10.1149/10701.2559ecst.

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Machine learning plays a vital role in the real-time cloud based medical computing systems. However, most of the computing servers are independent of data security and recovery scheme in multiple virtual machines due to high computing cost and time. Also these cloud based medical applications require static security parameters for cloud data security. Cloud based medical applications require multiple servers in order to store medical records or machine learning patterns for decision making. Due to high computational memory and time, these cloud systems require an efficient data security framework in order to provide strong data access control among the multiple users. In this paper, a hybrid cloud data security framework is developed to improve the data security on the large machine learning patterns in real-time cloud computing environment. This work is implemented in two phases, data replication phase and multi-user data access security phase. Initially, machine decision patterns are replicated among the multiple servers for data recovering phase. In the multi-access cloud data security framework, a hybrid multi-access key based data encryption and decryption model is implemented on the large machine learning medical patterns for data recovery and security process. Experimental results proved that the present two-phase data recovering and security framework has better computational efficiency than the conventional approaches on large medical decision patterns.

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Kong, Rui, Qiong Wang, Gu Yu Hu, and Zhi Song Pan. "Fuzzy Asymmetric Support Vector Machines." Advanced Materials Research 433-440 (January 2012): 7479–86. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.7479.

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Support Vector Machines (SVM) has been extensively studied and has shown remarkable success in many applications. However the success of SVM is very limited when it is applied to the problem of learning from imbalanced datasets in which negative instances heavily outnumber the positive instances (e.g. in medical diagnosis and detecting credit card fraud). In this paper, we propose the fuzzy asymmetric algorithm to augment SVMs to deal with imbalanced training-data problems, called FASVM, which is based on fuzzy memberships, combined with different error costs (DEC) algorithm. We compare the performance of our algorithm against these two algorithms, along with different error costs and regular SVM and show that our algorithm outperforms all of them.

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Habibu Ahmad Ibrahim, Yusuf Abubakar Maitama Hotoro, Abubakar Sani Garba, and Bushra Khan. "Successive infusion of Mncl2 in order to analyze the image produced by MRI machines." International Journal of Frontline Research in Chemistry and Pharmacy 1, no. 1 (July 30, 2022): 032–36. http://dx.doi.org/10.56355/ijfrcp.2022.1.1.0005.

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The use of MRI machines is a fast growing in the field of Medical Imaging. MRI machine operates on the principal of Nuclear Magnetic Resonance Imaging which can be explained by Quantum Mechanics or Classical Mechanics. Nuclear Magnetic Resonance Imaging is a process by which atomic nuclei containing protons and neutrons which are all inform of a magnetic field absorb and re-emit electromagnetic radiation. The energy of the emitted electromagnetic radiation is usually at a certain resonance frequency, which depends upon the strength of the magnetic field and the magnetic properties of the atoms. The resonance frequency produced is similar to radio frequency RF radiation, which when observed it produce a fine spectrum of anatomical structure of objects. MRI machines are currently used in hospitals and clinics to take the anatomical structures of the human body. And a wide variety of artifacts is routinely encountered on the images produced by this Machines. Manganese is a metal that was proposed to be use in NMRI machines, but due to it’s toxic nature and it is a heavy metal, it is not use at all. But we are able to produce metallic chloride of Mn2+ which over comes the toxicity of metal and behaves like a metallic Salt in the human body. However, we are able to successfully infuse MnCl2 into a Rat and a Rabbit due to its unique properties in order to analyse the images produced by a MRI Machine. Conclusively, we are able to observe that MnCl2 improves the images quality produced by the MRI Machine.

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Huang, Yucheng, Guangshun Chen, Jiyun Chen, Dalin Li, Yanchun Liang, and Wei Du. "Application of Support Vector Machines for Breast Calcification Cluster Detection and Mass Classification." Journal of Physics: Conference Series 2400, no. 1 (December 1, 2022): 012003. http://dx.doi.org/10.1088/1742-6596/2400/1/012003.

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Abstract Breast cancer has become “the most common cancer worldwide”, and it is an urgent problem in the medical field to improve the detection rate of breast cancer through early diagnosis and treatment. Based on the current research on medical image processing, our work selects breast images from the MIAS database for pre-processing, segmentation, texture feature extraction and classification, and conducts an in-depth investigation and experimental validation on the theoretical basis of support vector machine algorithm, kernel function selection, and key parameter optimization. The results show the effectiveness of support vector machines in detecting abnormal areas and classifying masses in breast images and provide research ideas for breast cancer diagnosis.

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Mello-Román, Jorge D., Julio C. Mello-Román, Santiago Gómez-Guerrero, and Miguel García-Torres. "Predictive Models for the Medical Diagnosis of Dengue: A Case Study in Paraguay." Computational and Mathematical Methods in Medicine 2019 (July 29, 2019): 1–7. http://dx.doi.org/10.1155/2019/7307803.

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Early diagnosis of dengue continues to be a concern for public health in countries with a high incidence of this disease. In this work, we compared two machine learning techniques: artificial neural networks (ANN) and support vector machines (SVM) as assistance tools for medical diagnosis. The performance of classification models was evaluated in a real dataset of patients with a previous diagnosis of dengue extracted from the public health system of Paraguay during the period 2012–2016. The ANN multilayer perceptron achieved better results with an average of 96% accuracy, 96% sensitivity, and 97% specificity, with low variation in thirty different partitions of the dataset. In comparison, SVM polynomial obtained results above 90% for accuracy, sensitivity, and specificity.

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Journal articles on the topic 'Medical Machines'

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