Artigos de revistas: "Biomedical analysis techniques"

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Kataoka, Hiroyuki. "SPME techniques for biomedical analysis". Bioanalysis 7, n.º 17 (setembro de 2015): 2135–44. http://dx.doi.org/10.4155/bio.15.145.

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Witte, H., e M. Wacker. "Time-frequency Techniques in Biomedical Signal Analysis". Methods of Information in Medicine 52, n.º 04 (2013): 279–96. http://dx.doi.org/10.3414/me12-01-0083.

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SummaryObjectives: This review outlines the method -ological fundamentals of the most frequently used non-parametric time-frequency analysis techniques in biomedicine and their main properties, as well as providing decision aids concerning their applications.Methods: The short-term Fourier transform (STFT), the Gabor transform (GT), the S-transform (ST), the continuous Morlet wavelet transform (CMWT), and the Hilbert transform (HT) are introduced as linear transforms by using a unified concept of the time-frequency representation which is based on a standardized analytic signal. The Wigner-Ville dis -tribution (WVD) serves as an example of the ‘quadratic transforms’ class. The combination of WVD and GT with the matching pursuit (MP) decomposition and that of the HT with the empirical mode decomposition (EMD) are explained; these belong to the class of signal-adaptive approaches.Results: Similarities between linear transforms are demonstrated and differences with regard to the time-frequency resolution and interference (cross) terms are presented in detail. By means of simulated signals the effects of different time-frequency resolutions of the GT, CMWT, and WVD as well as the resolution-related properties of the inter -ference (cross) terms are shown. The method-inherent drawbacks and their consequences for the application of the time-frequency techniques are demonstrated by instantaneous amplitude, frequency and phase measures and related time-frequency representations (spectrogram, scalogram, time-frequency distribution, phase-locking maps) of measured magnetoencephalographic (MEG) signals.Conclusions: The appropriate selection of a method and its parameter settings will ensure readability of the time-frequency representations and reliability of results. When the time-frequency characteristics of a signal strongly correspond with the time-frequency resolution of the analysis then a method may be considered ‘optimal’. The MP-based signal-adaptive approaches are preferred as these provide an appropriate time-frequency resolution for all frequencies while simultaneously reducing interference (cross) terms.

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Malet-Martino, M., e U. Holzgrabe. "NMR techniques in biomedical and pharmaceutical analysis". Journal of Pharmaceutical and Biomedical Analysis 55, n.º 1 (abril de 2011): 1–15. http://dx.doi.org/10.1016/j.jpba.2010.12.023.

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Szultka, Malgorzata, Pawel Pomastowski, Viorica Railean-Plugaru e Boguslaw Buszewski. "Microextraction sample preparation techniques in biomedical analysis". Journal of Separation Science 37, n.º 21 (25 de setembro de 2014): 3094–105. http://dx.doi.org/10.1002/jssc.201400621.

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Kataoka, Hiroyuki, e Keita Saito. "Recent advances in SPME techniques in biomedical analysis". Journal of Pharmaceutical and Biomedical Analysis 54, n.º 5 (abril de 2011): 926–50. http://dx.doi.org/10.1016/j.jpba.2010.12.010.

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Turnell, David C., e John D. H. Cooper. "Automation of liquid chromatographic techniques for biomedical analysis". Journal of Chromatography B: Biomedical Sciences and Applications 492 (agosto de 1989): 59–83. http://dx.doi.org/10.1016/s0378-4347(00)84464-3.

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Cerutti, S. "On Time-frequency Techniques in Biomedical Signal Analysis". Methods of Information in Medicine 52, n.º 04 (2013): 277–78. http://dx.doi.org/10.1055/s-0038-1627060.

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Abaid Mahdi, Muhammed, e Samaher Al_Janabi. "Evaluation prediction techniques to achieve optimal biomedical analysis". International Journal of Grid and Utility Computing 1, n.º 1 (2019): 1. http://dx.doi.org/10.1504/ijguc.2019.10020511.

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Scriba, Gerhard K. E. "Chiral electromigration techniques in pharmaceutical and biomedical analysis". Bioanalytical Reviews 3, n.º 2-4 (27 de setembro de 2011): 95–114. http://dx.doi.org/10.1007/s12566-011-0024-3.

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Kalish, Heather, e Terry Phillips. "The Application of Micro-Analytical Techniques to Biomedical Analysis". Current Pharmaceutical Analysis 5, n.º 3 (1 de agosto de 2009): 208–28. http://dx.doi.org/10.2174/157341209788922057.

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Janabi, Samaher Al, e Muhammed Abaid Mahdi. "Evaluation prediction techniques to achievement an optimal biomedical analysis". International Journal of Grid and Utility Computing 10, n.º 5 (2019): 512. http://dx.doi.org/10.1504/ijguc.2019.102021.

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Renukalatha, S., e K. V. Suresh. "A REVIEW ON BIOMEDICAL IMAGE ANALYSIS". Biomedical Engineering: Applications, Basis and Communications 30, n.º 04 (agosto de 2018): 1830001. http://dx.doi.org/10.4015/s1016237218300018.

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Bio-medical image analysis is an interdisciplinary field which includes: biology, physics, medicine and engineering. It deals with application of image processing techniques to biological or medical problems. Medical images to be analyzed contain a lot of information regarding the anatomical structure under investigation to reveal valid diagnosis and thereby helping doctors to choose adequate therapy. Doctors usually analyse these medical images manually through visual interpretation. But visual analysis of these images by human observers is limited due to variation in interpersonal interpretations, fatigue errors, surrounding disturbances and moreover this kind of analysis is purely subjective. On the other hand, automated analysis of these images using computers with suitable techniques favours the objective analysis by an expert and thereby improving the diagnostic confidence and accuracy of analysis. This survey is a consolidation of the exhaustive literature records related to biomedical image analysis.

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Shams, Mudassir, e Bruno Carpentieri. "Computational Analysis of Parallel Techniques for Nonlinear Biomedical Engineering Problems". Algorithms 17, n.º 12 (14 de dezembro de 2024): 575. https://doi.org/10.3390/a17120575.

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In this study, we develop new efficient parallel techniques for solving both distinct and multiple roots of nonlinear problems at the same time. The parallel techniques represent an innovative contribution to the discipline, with local convergence of the ninth order. Theoretical research shows the rapid convergence and effectiveness of the proposed parallel schemes. To assess the suggested scheme’s stability and consistency, we look at certain biomedical engineering applications, such as osteoporosis in Chinese women, blood rheology, and differential equations. Overall, detailed analyses of convergence behavior, memory utilization, computational time, and percentage computational efficiency show that the novel parallel techniques outperform the traditional methods. The proposed methods would be more suitable for large-scale computational problems in biomedical applications due to their advantages in memory efficiency, CPU time, and error reduction.

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Nayak, Janmenjoy, Bighnaraj Naik, Pandit Byomakesha Dash e Danilo Pelusi. "Optimal Fuzzy Cluster Partitioning by Crow Search Meta-Heuristic for Biomedical Data Analysis". International Journal of Applied Metaheuristic Computing 12, n.º 2 (abril de 2021): 49–66. http://dx.doi.org/10.4018/ijamc.2021040104.

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Biomedical data is often more unstructured in nature, and biomedical data processing task is becoming more complex day by day. Thus, biomedical informatics requires competent data analysis and data mining techniques for designing decision support system's framework to solve clinical and heathcare-related issues. Due to increasingly large and complex data sets and demand of biomedical informatics research, researchers are attracted towards automated machine learning models. This paper is proposed to design an efficient machine learning model based on fuzzy c-means with meta-heuristic optimizations for biomedical data analysis and clustering. The main contributions of this paper are 1) projecting an efficient machine learning model based on fuzzy c-means and meta-heuristic optimization for biomedical data classification, 2) employing benchmark validation techniques and critical hypothesises testing, and 3) providing a background for biomedical data processing with a view of data processing and mining.

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Gajare, Milind, e Shedge D.K. "CMOS Trans Conductance based Instrumentation Amplifier for Various Biomedical Signal Analysis". NeuroQuantology 20, n.º 5 (30 de abril de 2022): 53–60. http://dx.doi.org/10.14704/nq.2022.20.5.nq22148.

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Feed forward design techniques for the Trans-conductance operational amplifier removes the barriers of operating frequencies. It is now possible to design amplifiers with large the Trans-conductance that operates at Giga hertz frequency range. There are several Trans-conductance amplifiers used to design a medical and Industrial application that helps in processing various bio medical signals such as Electrocardiographs, Electroencephalographs, Electromyograms and several others. The proposed paper shows the implementation of an instrumentation amplifier using CMOS based the Trans-conductance operational amplifiers also the processing of biomedical ECG, EEG and EMG signals. The CMOS process technology helps to integrate complex circuits on minimal surface area. The Trans-conductance instrumentation operational amplifiers has features includes noise reduction, low DC offset, High output impedance and Common Mode rejection Ratio values. The circuit implementation and simulations has been done on Electronic Design and Automation tool with 0.13μm CMOS process technology.

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Mazing, Mariia S., Anna Yu Zaitceva e Lev V. Novikov. "Analysis of data from biomedical multisensor optical systems". Journal of Optical Technology 91, n.º 7 (1 de julho de 2024): 509. https://doi.org/10.1364/jot.91.000509.

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Subject of study. This study investigates multisensor optical systems developed for biomedical research, focusing on methodologies for applying a multisensor approach to optical biomedical diagnostics. Aim of study. The study aims to design and perform a comprehensive analysis of a multichannel optical system for collecting, transmitting, and analyzing diagnostic data. Additionally, it seeks to develop an effective algorithm for preprocessing large volumes of optical signals that characterize the state of biological objects using data mining techniques. Method. The study applies multidimensional data mining techniques to implement a multisensor approach to ranking optical spectroscopy signals. Main results. A compact optical multisensor system designed for biomedical diagnostics is introduced. This system features an array of 18 photodiode-sensitive elements with selective sensitivity to optical radiation in the visible and infrared ranges (410–940 nm). The study outlines the analytical stages for processing multidimensional information obtained from the system, incorporating principal component analysis and cluster analysis algorithms. Experimental studies involving human participants validated the efficacy of the proposed methodologies. Using data mining techniques, the study visualized ranked subject data, uncovering hidden patterns in the functional states of microcirculatory tissue systems based on sensor array readings. Practical significance. The findings have significant practical implications for the development of automated systems incorporating optical multisensor technologies. These systems can address challenges associated with identifying and analyzing the functional states of complex multicomponent biological tissues and fluids in the human body.

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Monika, Rajesh kr Katare e SBL Tripathi. "Analysis of Silver Nanoparticles Synthesis, Characterization, and Biomedical Applications". RESEARCH HUB International Multidisciplinary Research Journal 11, n.º 4 (30 de abril de 2024): 5–12. http://dx.doi.org/10.53573/rhimrj.2024.v11n4.002.

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This paper presents a comprehensive examination of the synthesis, characterization, and applications of silver nanoparticles (AgNPs) in biomedical fields. AgNPs exhibit exceptional properties, including antibacterial, antiviral, and antifungal activities, rendering them valuable in various biomedical applications. We explore diverse synthesis methods—chemical, physical, and biological—detailing their advantages and challenges. Through bibliometric analysis of 10,278 publications spanning 2010 to 2020, we identify trends in AgNPs research and synthesis techniques. Characterization methods crucial for understanding AgNPs' physicochemical properties are discussed, encompassing spectroscopic, microscopic, and physicochemical analyses. We employ bibliometric clustering to elucidate AgNPs' biomedical applications, which include antibacterial, antiviral, anticancer, bone healing, bone cement, dental, and wound healing applications. Our findings underscore the growing adoption of AgNPs in biomedicine due to their multifaceted properties and demonstrated efficacy. By examining synthesis methods, characterization techniques, and applications, this paper contributes to a deeper understanding of AgNPs' role in advancing biomedical technologies. AgNPs offer promising solutions to various biomedical challenges, reflecting their increasing relevance in healthcare. This analysis provides insights into current research directions and highlights AgNPs' potential for addressing critical healthcare needs.

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Rajagopal, Sivakumar, Waarish Arpan, Stefy Thomas, Gajanan Gomare e Rahul Soangra. "Comparison and Analysis of Different Thermography Techniques in the Biomedical Applications". ECS Transactions 107, n.º 1 (24 de abril de 2022): 9403–16. http://dx.doi.org/10.1149/10701.9403ecst.

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Thermography is a technique that involves using a thermal camera to make a thermogram image that depicts the quantity of infrared energy emitted, transmitted, and reflected by an object. Body surface temperature monitoring, which varies when blood flow increases or decreases due to clinical irregularities, has been frequently utilised to diagnose medical problems such as breast cancer, diabetes neuropathy, and peripheral vascular disorders using thermography. Thermography has become a significant tool, particularly for fever screening during infectious disease epidemics such as Ebola and COVID-19, due to its non-invasive and non-contact nature. Thermography is a sensory instrument that can be particularly valuable in protecting human health when paired with thermal physiology data. In this review, we analyze and compare several thermography processes and aspects to come up with the optimal methodology for use in the medical field.

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Baeyens, WillyR G. "Fluorometric analysis in biomedical chemistry -Trends and techniques including HPLC applications". Journal of Chromatography A 590, n.º 2 (janeiro de 1992): 373–74. http://dx.doi.org/10.1016/0021-9673(92)85402-f.

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HUANG, ChengZhi, JiaLi XU e ZuHong XIONG. "Two-photon techniques and their applications in biomedical and pharmaceutical analysis". Chinese Science Bulletin 56, n.º 6 (1 de março de 2011): 361–69. http://dx.doi.org/10.1360/972010-1263.

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Gooijer, Cees. "Fluorometric Analysis in Biomedical Chemistry—Trends and Techniques including HPLC Applications". Analytica Chimica Acta 264, n.º 2 (julho de 1992): 369. http://dx.doi.org/10.1016/0003-2670(92)87027-i.

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Rogante, Massimo. "Analysis of biomedical materials and parts: Advanced nano(micro)-characterization by neutron beam techniques". Zastita materijala 63, n.º 2 (2022): 146–52. http://dx.doi.org/10.5937/zasmat2202146r.

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The progress of the study of biomedical materials and devices, as well as their advancement, especially depend on the application of efficient characterization techniques to evaluate key physical parameters connected to performances, damage and quality. A main aim is to establish correct relationships between macroscopic functional properties and nano(micro)-characteristics. Numerous invasive biomedical devices, e.g., as planned to remain in the human body for the entire life of the patient, once implanted, operate in the ionic environment of the blood and in contact with the released substances and cells. The consequent effects must be added to the other aging factors: the dynamic stress of the pulsation is one of these effects and concerns the operational of self-expandable stents installed in arteries such as the carotid to correct stenosis. Neutron beam techniques are an excellent tool to study materials and parts of biomedical interest, contributing to solve important questions linked with the methodological restrictions of the analysis methods generally adopted: their results, complementarily, can help improving quality and functionality. This paper concerns the advanced nano(micro)-characterization of biomedical materials and parts by these non-destructive and non-invasive nuclear methods. Some examples related to the biological field are also mentioned. For applications in the biomedical and in the industrial sectors, the Rogante Engineering Office has developed particular methodological approaches and dedicated processing and treatment procedures.

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Kokil, Sachin, e Manish Bhatia. "Antifungal Azole Metabolites: Significance in Pharmaceutical and Biomedical Analysis". Journal of Medical Biochemistry 28, n.º 1 (1 de janeiro de 2009): 1–10. http://dx.doi.org/10.2478/v10011-008-0040-1.

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Antifungal Azole Metabolites: Significance in Pharmaceutical and Biomedical Analysis Individualised therapy and factors determining such variability among patients are confusing to both physicians and their patients because of the observed therapeutic, metabolic and toxic response. The same is true about antifungal azoles. They are under the influence and become targets of metabolic drug-drug interactions where more than one active form of the drug may be involved. The clinical relevance of these interactions may vary upon the azole involved and upon the intention of drug administration. The pharmacodynamics and pharmacokinetics of azole drugs as indicated by the reviewed data make the need for characterization of all their metabolites even more evident. The health care systems also emphasize the identification and quantitation of the metabolites for a comprehensive understanding of the biological safety of individual metabolites, thus, revealing the need and scope of bioanalytical research in metabolite and toxicity profiling of drugs. Availability of protocols for qualitative and quantitative characterization of all metabolites will have many applications for therapeutic drug monitoring, bioequivalence, toxicological and all related studies. Identification of metabolites may be done by a variety of chromatographic and spectroscopic techniques, either alone or in combination with other techniques. Conventional liquid chromatography has been exploited widely in the field of metabolite profiling. The arrival of hyphenated techniques has revolutionized metabolite profiling, by not only separating but also generating data for the structural identification of metabolites as well. Among all techniques, the most exploited are Liquid Chromatography-Mass Spectroscopy, Nuclear Magnetic Resonance spectroscopy, Liquid Chromatography-Nuclear Magnetic Resonance spectroscopy, Liquid Chromatography-Nuclear Magnetic Resonance spectroscopy-Mass Spectroscopy and Extraction-Nuclear Magnetic Resonance spectroscopy. This compilation provides a tool for the metabolic, bioanalytical and biomedical understanding of antifungal azole metabolites.

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Oza, Parita, Paawan Sharma, Samir Patel, Festus Adedoyin e Alessandro Bruno. "Image Augmentation Techniques for Mammogram Analysis". Journal of Imaging 8, n.º 5 (20 de maio de 2022): 141. http://dx.doi.org/10.3390/jimaging8050141.

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Research in the medical imaging field using deep learning approaches has become progressively contingent. Scientific findings reveal that supervised deep learning methods’ performance heavily depends on training set size, which expert radiologists must manually annotate. The latter is quite a tiring and time-consuming task. Therefore, most of the freely accessible biomedical image datasets are small-sized. Furthermore, it is challenging to have big-sized medical image datasets due to privacy and legal issues. Consequently, not a small number of supervised deep learning models are prone to overfitting and cannot produce generalized output. One of the most popular methods to mitigate the issue above goes under the name of data augmentation. This technique helps increase training set size by utilizing various transformations and has been publicized to improve the model performance when tested on new data. This article surveyed different data augmentation techniques employed on mammogram images. The article aims to provide insights into basic and deep learning-based augmentation techniques.

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DEBBAL, S. M., e F. BEREKSI-REGUIG. "SECOND CARDIAC SOUND ANALYSIS TECHNIQUES AND PERFORMANCE COMPARISON". Journal of Mechanics in Medicine and Biology 05, n.º 03 (setembro de 2005): 429–42. http://dx.doi.org/10.1142/s021951940500162x.

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This paper presents the applications of the spectrogram, Wigner distribution and wavelet transform analysis methods to the second cardiac sound S2 of the phonocardiogram signal (PCG). A comparison between these methods has shown the resolution differences between them. It is found that the spectrogram Short-Time Fourier Transform (STFT) cannot detect the two internals components of the second sound S2 (A2 and P2, atrial and pulmonary components respectively). The Wigner Distribution (WD) can provide time-frequency characteristics of the sound S2, but with insufficient diagnostic information as the two components (A2 and P2) are not accurately detected, appearing to be one component only. It is found that the wavelet transform (WT) is capable of detecting the two components, the aortic valve component A2 and pulmonary valve component P2, of the second cardiac sound S2. However, the standard Fourier transform can display these components in frequency but not the time delay between them. Furthermore, the wavelet transform provides more features and characteristics of the second sound S2 that will hemp physicians to obtain qualitative and quantitative measurements of the time-frequency characteristics.

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Sousa, Jose Vigno Moura, Vilson Rosa de Almeida, Aratã Andrade Saraiva, Felipe Miranda de Jesus Castro, Domingos Bruno Sousa Santos e Pedro Mateus Cunha Pimentel. "Comparison between transforms a behavior qualitative analysis of various biomedical signals". Research, Society and Development 9, n.º 10 (27 de setembro de 2020): e3179108657. http://dx.doi.org/10.33448/rsd-v9i10.8657.

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This paper aims to compare the behave of different signals when applied to different compression techniques, to test and find the best compression techniques to each different signal, also proving that different signals behave differently in distinct types of compression, the results of this work was satisfactory to prove that different types of compression can be used on signals to achieve better results.

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Yaqoob, Abrar, Rabia Musheer Aziz, Navneet Kumar Verma, Praveen Lalwani, Akshara Makrariya e Pavan Kumar. "A Review on Nature-Inspired Algorithms for Cancer Disease Prediction and Classification". Mathematics 11, n.º 5 (21 de fevereiro de 2023): 1081. http://dx.doi.org/10.3390/math11051081.

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In the era of healthcare and its related research fields, the dimensionality problem of high-dimensional data is a massive challenge as it is crucial to identify significant genes while conducting research on diseases like cancer. As a result, studying new Machine Learning (ML) techniques for raw gene expression biomedical data is an important field of research. Disease detection, sample classification, and early disease prediction are all important analyses of high-dimensional biomedical data in the field of bioinformatics. Recently, machine-learning techniques have dramatically improved the analysis of high-dimension biomedical data sets. Nonetheless, researchers’ studies on biomedical data faced the challenge of vast dimensions, i.e., the vast features (genes) with a very low sample space. In this paper, two-dimensionality reduction methods, feature selection, and feature extraction are introduced with a systematic comparison of several dimension reduction techniques for the analysis of high-dimensional gene expression biomedical data. We presented a systematic review of some of the most popular nature-inspired algorithms and analyzed them. The paper is mainly focused on the original principles behind each of the algorithms and their applications for cancer classification and prediction from gene expression data. Lastly, the advantages and disadvantages of nature-inspired algorithms for biomedical data are evaluated. This review paper may guide researchers to choose the most effective algorithm for cancer classification and prediction for the satisfactory analysis of high-dimensional biomedical data.

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Dabir, Aishwarya, Pratiksha Khedkar, Laxmi Panch, Tejal Thakare e Dr M. A. Pradhan. "Analysis of Cardiovascular Disease using Machine Learning Techniques". International Journal for Research in Applied Science and Engineering Technology 11, n.º 5 (31 de maio de 2023): 4901–5. http://dx.doi.org/10.22214/ijraset.2023.52789.

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Abstract: Detecting cardiovascular disease early is crucial in healthcare, especially in the field of cardiology. With 12 million deaths worldwide annually, the disease is a significant health concern. Early detection can lead to lifestyle changes that reduce the risk of complications. Machine learning techniques can be used to extract useful data from large datasets and make accurate predictions, requiring less investment. Machine learning algorithms can also be used to address unbalanced datasets and feature selection, which can improve diagnostic accuracy. Using ensemble learning with a machine learning algorithm, feature selection, and biomedical test values can help classify cardiovascular disease. Multiple classifier models can also be applied to improve accuracy with an ensemble classifier.

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Liu, Zengxin, Caiwen Ma, Wenji She e Meilin Xie. "Biomedical Image Segmentation Using Denoising Diffusion Probabilistic Models: A Comprehensive Review and Analysis". Applied Sciences 14, n.º 2 (11 de janeiro de 2024): 632. http://dx.doi.org/10.3390/app14020632.

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Biomedical image segmentation plays a pivotal role in medical imaging, facilitating precise identification and delineation of anatomical structures and abnormalities. This review explores the application of the Denoising Diffusion Probabilistic Model (DDPM) in the realm of biomedical image segmentation. DDPM, a probabilistic generative model, has demonstrated promise in capturing complex data distributions and reducing noise in various domains. In this context, the review provides an in-depth examination of the present status, obstacles, and future prospects in the application of biomedical image segmentation techniques. It addresses challenges associated with the uncertainty and variability in imaging data analyzing commonalities based on probabilistic methods. The paper concludes with insights into the potential impact of DDPM on advancing medical imaging techniques and fostering reliable segmentation results in clinical applications. This comprehensive review aims to provide researchers, practitioners, and healthcare professionals with a nuanced understanding of the current state, challenges, and future prospects of utilizing DDPM in the context of biomedical image segmentation.

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Sáiz-Manzanares, María Consuelo, Raúl Marticorena-Sánchez, María Camino Escolar-Llamazares, Irene González-Díez e Rut Velasco-Saiz. "Using Serious Game Techniques with Health Sciences and Biomedical Engineering Students: An Analysis Using Machine Learning Techniques". Information 15, n.º 12 (12 de dezembro de 2024): 804. https://doi.org/10.3390/info15120804.

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The use of serious games on virtual learning platforms as a learning support resource is increasingly common. They are especially effective in helping students acquire mainly applied curricular content. However, a process is required to monitor the effectiveness and students’ perceived satisfaction. The objectives of this study were to (1) identify the most significant characteristics; (2) determine the most relevant predictors of learning outcomes; (3) identify groupings with respect to the different serious game activities; and (4) to determine students’ perceptions of the usefulness of the simple and complex serious game activities. We worked with a sample of 130 university students studying health sciences and biomedical engineering. The serious game activities were applied in a Moodle environment, UBUVirtual, and monitored using the UBUMonitor tool. The degree type and the type of serious game explained differing percentages of the variance in the learning results in the assessment tests (34.4%—multiple choice tests [individual assessment]; 11.2%—project performance [group assessment]; 25.6%—project presentation [group assessment]). Different clusters were found depending on the group of students and the algorithm applied. The Adjusted Rang Index was applied to determine the most appropriate algorithm in each case. The student satisfaction was high in all the cases. However, they indicated complex serious games as being more useful than simple serious games as learning resources for the practical content in both health sciences and biomedical engineering degrees.

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Porcaro, Francesco, Stéphane Roudeau, Asuncion Carmona e Richard Ortega. "Advances in element speciation analysis of biomedical samples using synchrotron-based techniques". TrAC Trends in Analytical Chemistry 104 (julho de 2018): 22–41. http://dx.doi.org/10.1016/j.trac.2017.09.016.

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Feldman, Ronen, Yizhar Regev, Eyal Hurvitz e Michal Finkelstein-Landau. "Mining the biomedical literature using semantic analysis and natural language processing techniques". BIOSILICO 1, n.º 2 (maio de 2003): 69–80. http://dx.doi.org/10.1016/s1478-5382(03)02330-8.

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Edwards, Lloyd J. "Modern statistical techniques for the analysis of longitudinal data in biomedical research". Pediatric Pulmonology 30, n.º 4 (2000): 330–44. http://dx.doi.org/10.1002/1099-0496(200010)30:4<330::aid-ppul10>3.0.co;2-d.

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Kora, Padmavathi, Chui Ping Ooi, Oliver Faust, U. Raghavendra, Anjan Gudigar, Wai Yee Chan, K. Meenakshi, K. Swaraja, Pawel Plawiak e U. Rajendra Acharya. "Transfer learning techniques for medical image analysis: A review". Biocybernetics and Biomedical Engineering 42, n.º 1 (janeiro de 2022): 79–107. http://dx.doi.org/10.1016/j.bbe.2021.11.004.

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Magar, Satyawati, e Bhavani Sridharan. "Comparative analysis of various Image compression techniques for Quasi Fractal lossless compression". International Journal of Computer Communication and Informatics 2, n.º 2 (30 de outubro de 2020): 30–45. http://dx.doi.org/10.34256/ijcci2024.

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The most important Entity to be considered in Image Compression methods are Paek to signal noise ratio and Compression ratio. These two parameters are considered to judge the quality of any Image.and they a play vital role in any Image processing applications. Biomedical domain is one of the critical areas where more image datasets are involved for analysis and biomedical image compression is very, much essential. Basically, compression techniques are classified into lossless and lossy. As the name indicates, in the lossless technique the image is compressed without any loss of data. But in the lossy, some information may loss. Here both lossy & lossless techniques for an image compression are used. In this research different compression approaches of these two categories are discussed and brain images for compression techniques are highlighted. Both lossy and lossless techniques are implemented by studying it’s advantages and disadvantages. For this research two important quality parameters i.e. CR & PSNR are calculated. Here existing techniques DCT, DFT, DWT & Fractal are implemented and introduced new techniques i.e Oscillation Concept method, BTC-SPIHT & Hybrid technique using adaptive threshold & Quasi Fractal Algorithm.

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Cunha, Naelso Alves, Ana Vitória de Morais Inocêncio, Erico Leite Cavalcante, Gilson José Alves, Marilú Gomes Netto Monte da Silva, Malki-Çedheq Benjamim Celso da Silva e Marco Aurélio Benedetti Rodrigues. "Computer vision: applications in Biomedical Engineering". Caderno Pedagógico 21, n.º 13 (4 de dezembro de 2024): e11502. https://doi.org/10.54033/cadpedv21n13-056.

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The focus of this study is the presentation of two systems, which use computer vision techniques. In the first, the authors applied these techniques to the acquisition and processing system of ovitrap images. However, the second system is a physiotherapeutic evaluation platform for dynamic monitoring of body balance. By using a depth image of the patient (based on a 3D camera), the algorithm can predict the exact positions of the joints of an individual, without temporal information. The two studies described presented showed promising results, which demonstrated that computer vision techniques are of great importance. The experiments with the Aedes Aegypti mosquito egg has allowed accurate detection and counting of them. The experiments with body balance analysis has allowed the tracking of the center of mass of an individual during physiotherapeutic exercises. Software has detected the movement of the center of mass, satisfying a physiotherapeutic need. The techniques developed for computer vision have many possible applications in different areas and different populations, not only in the areas presented in this study.

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Chen, Xuequan, Hannah Lindley-Hatcher, Rayko I. Stantchev, Jiarui Wang, Kaidi Li, Arturo Hernandez Serrano, Zachary D. Taylor, Enrique Castro-Camus e Emma Pickwell-MacPherson. "Terahertz (THz) biophotonics technology: Instrumentation, techniques, and biomedical applications". Chemical Physics Reviews 3, n.º 1 (março de 2022): 011311. http://dx.doi.org/10.1063/5.0068979.

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Terahertz (THz) technology has experienced rapid development in the past two decades. Growing numbers of interdisciplinary applications are emerging, including materials science, physics, communications, and security as well as biomedicine. THz biophotonics involves studies applying THz photonic technology in biomedicine, which has attracted attention due to the unique features of THz waves, such as the high sensitivity to water, resonance with biomolecules, favorable spatial resolution, capacity to probe the water–biomolecule interactions, and nonionizing photon energy. Despite the great potential, THz biophotonics is still at an early stage of development. There is a lack of standards for instrumentation, measurement protocols, and data analysis, which makes it difficult to make comparisons among all the work published. In this article, we give a comprehensive review of the key findings that have underpinned research into biomedical applications of THz technology. In particular, we will focus on the advances made in general THz instrumentation and specific THz-based instruments for biomedical applications. We will also discuss the theories describing the interaction between THz light and biomedical samples. We aim to provide an overview of both basic biomedical research as well as pre-clinical and clinical applications under investigation. The paper aims to provide a clear picture of the achievements, challenges, and future perspectives of THz biophotonics.

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Kumar, Singh Amit, e Jain Tushar. "Review of 3D Printing Applications in Biomedical Engineering: A Comprehensive Analysis". Journal of Clinical and Biomedical Sciences 14, n.º 4 (30 de abril de 2024): 129–37. https://doi.org/10.58739/jcbs/v14i4.110.

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Three-dimensional printing (3DP), also known as additive manufacturing, has significantly impacted the biomedical field by enabling the creation of complex, patient-specific medical devices, implants, and tissues. The need for advanced medical solutions due to an aging population and increased reliance on electronic gadgets has driven research into 3DP application. This review focuses on the various biomedical applications of 3DP, including drug synthesis, medical device fabrication, bioprinting, and surgical planning. The review discusses key techniques such as bioprinting, which combines cells, growth factors, and biomaterials to create tissue-like structures, and the use of 3DP for patient-specific prostheses and orthoses. Additionally, the role of 3DP in tissue engineering, organ printing, and the development of bioactive and biodegradable scaffolds is explored. The findings highlight the versatility of 3DP in creating patient-specific medical devices, enhancing surgical outcomes, and advancing tissue engineering and regenerative medicine. Different 3DP techniques discussed also shows promise in producing robust and biocompatible implants, while challenges remain in the widespread application of bio printed organs and tissues. 3DP has the potential to revolutionize the biomedical field by providing customized, efficient, and effective solutions for various medical challenges. Keywords: Three-dimensional printing, Bioprinting, Biomedical applications, Tissue engineering, Patient-specific implants, Regenerative medicine, Additive manufacturing

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Biswas, Deblina, Swarup Roy e Srivathsan Vasudevan. "Biomedical Application of Photoacoustics: A Plethora of Opportunities". Micromachines 13, n.º 11 (3 de novembro de 2022): 1900. http://dx.doi.org/10.3390/mi13111900.

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The photoacoustic (PA) technique is a non-invasive, non-ionizing hybrid technique that exploits laser irradiation for sample excitation and acquires an ultrasound signal generated due to thermoelastic expansion of the sample. Being a hybrid technique, PA possesses the inherent advantages of conventional optical (high resolution) and ultrasonic (high depth of penetration in biological tissue) techniques and eliminates some of the major limitations of these conventional techniques. Hence, PA has been employed for different biomedical applications. In this review, we first discuss the basic physics of PA. Then, we discuss different aspects of PA techniques, which includes PA imaging and also PA frequency spectral analysis. The theory of PA signal generation, detection and analysis is also detailed in this work. Later, we also discuss the major biomedical application area of PA technique.

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Cruzado-Oliva, Fredy, Heber Arbildo-Vega, Edward Infantes-Ruíz, Jhonatan Rodríguez-Angulo, Luis Alarco-La Rosa e Saurav Panda. "Effectiveness of cordless techniques in gingival displacement. A systematic review and meta-analysis". Journal of Oral Research 12, n.º 1 (31 de dezembro de 2023): 257–76. http://dx.doi.org/10.17126/joralres.2023.023.

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Objective: To compare the effectiveness of the conventional technique and cordless technique in gingival displacement. Materials and Methods: A bibliographic search was carried out until August 2023, in the biomedical databases: Pubmed/Medline, Cochrane Library, Scielo, Scopus and Google Scholar. Included studies reporting the gingival displacement of vital teeth using the cordless and con-ventional techniques comprised clinical trials, articles in English and without time limits. The RoB 2.0 tool was used to assess the risk of the included studies and the GRADEPro GDT tool to assess the quality of the evidence and the strength of recommendation of the results. Results: The preliminary search yielded a total of 489 articles, discarding those that did not meet the selection criteria, leaving only 15 articles. A total of fourteen articles entered a meta-analysis. It was found that the conventional technique caused better gingival (width) displacement than the cordless techniques, however, it caused more bleeding. Furthermore, among the wireless techniques, the one using polyvinylsiloxane obtained better results. Conclusions: The literature reviewed suggests that the conventional technique resulted in a better gingival displacement (width) than the cordless techniques, however, it causes a greater periodontal injury. Keywords: Periodontal Diseases; Oral Surgical Procedures; Gingiva; Gingival Recession; Systematic Review; Meta-analysis

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Padhee, Sourav, e Sakir Ahmed. "Application of statistics in biomedical research". Journal of Integrative Medicine and Research 2, n.º 2 (abril de 2024): 66–71. http://dx.doi.org/10.4103/jimr.jimr_1_24.

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Abstract Statistical tools for data analysis vary depending on the kind of data and measurement scales used. The objective of this review is to offer a deep insight into these various data types and measuring systems. This overview offers comprehensive details on the various data kinds and measurement scales along with examples. Applying the proper statistical techniques and drawing reliable conclusions require knowledge of the relevant data type or analysis procedure.

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SOSAN, RAAZIA, MUHAMMAD MOBEEN MOVANIA e SHAMA SIDDIQUI. "Perceptual analysis of distance sampling and transmittance estimation techniques in biomedical volume visualization". Turkish Journal of Electrical Engineering and Computer Sciences 30, n.º 6 (1 de janeiro de 2022): 2109–23. http://dx.doi.org/10.55730/1300-0632.3928.

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Moro, R., e G. Gialanella. "Nuclear Techniques for Trace Element Analysis. PIXE and its Applications to Biomedical Samples". Physica Scripta T32 (1 de janeiro de 1990): 233–36. http://dx.doi.org/10.1088/0031-8949/1990/t32/040.

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Scriba, Gerhard K. E. "Fundamental aspects of chiral electromigration techniques and application in pharmaceutical and biomedical analysis". Journal of Pharmaceutical and Biomedical Analysis 55, n.º 4 (junho de 2011): 688–701. http://dx.doi.org/10.1016/j.jpba.2010.11.018.

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Tabani, Hadi, Saeed Nojavan, Michal Alexovič e Ján Sabo. "Recent developments in green membrane-based extraction techniques for pharmaceutical and biomedical analysis". Journal of Pharmaceutical and Biomedical Analysis 160 (outubro de 2018): 244–67. http://dx.doi.org/10.1016/j.jpba.2018.08.002.

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Fanali, Chiara, Susanna Della Posta, Alessandra Gentili, Bezhan Chankvetadze e Salvatore Fanali. "Recent developments in electromigration techniques related to pharmaceutical and biomedical analysis – A review". Journal of Pharmaceutical and Biomedical Analysis 235 (outubro de 2023): 115647. http://dx.doi.org/10.1016/j.jpba.2023.115647.

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Jiji, G. Wiselin. "Analysis of lesions in multiple sclerosis using image processing techniques". International Journal of Biomedical Engineering and Technology 19, n.º 2 (2015): 118. http://dx.doi.org/10.1504/ijbet.2015.072932.

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Treo, E. F., C. J. Felice, M. C. Tirado, M. E. Valentinuzzi e D. O. Cervantes. "Comparative Analysis of Hematocrit Measurements by Dielectric and Impedance Techniques". IEEE Transactions on Biomedical Engineering 52, n.º 3 (março de 2005): 549–52. http://dx.doi.org/10.1109/tbme.2004.843297.

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Kaynak, Akif, e Ali Zolfagharian. "Functional Polymers in Sensors and Actuators: Fabrication and Analysis". Polymers 12, n.º 7 (15 de julho de 2020): 1569. http://dx.doi.org/10.3390/polym12071569.

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Recent advances in fabrication techniques have enabled the production of different types of polymer sensors and actuators that can be utilized in a wide range of applications, such as soft robotics, biomedical, smart textiles and energy harvesting [...]

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Calvo, Rodrigo, Isabel Rodriguez Mariblanca, Valerio Pini, Monica Dias, Virginia Cebrian, Andreas Thon, Asis Saad et al. "Novel Characterization Techniques for Multifunctional Plasmonic–Magnetic Nanoparticles in Biomedical Applications". Nanomaterials 13, n.º 22 (11 de novembro de 2023): 2929. http://dx.doi.org/10.3390/nano13222929.

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In the rapidly emerging field of biomedical applications, multifunctional nanoparticles, especially those containing magnetic and plasmonic components, have gained significant attention due to their combined properties. These hybrid systems, often composed of iron oxide and gold, provide both magnetic and optical functionalities and offer promising avenues for applications in multimodal bioimaging, hyperthermal therapies, and magnetically driven selective delivery. This paper focuses on the implementation of advanced characterization methods, comparing statistical analyses of individual multifunctional particle properties with macroscopic properties as a way of fine-tuning synthetic methodologies for their fabrication methods. Special emphasis is placed on the size-dependent properties, biocompatibility, and challenges that can arise from this versatile nanometric system. In order to ensure the quality and applicability of these particles, various novel methods for characterizing the magnetic gold particles, including the analysis of their morphology, optical response, and magnetic response, are also discussed, with the overall goal of optimizing the fabrication of this complex system and thus enhancing its potential as a preferred diagnostic agent.

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