Relevant bibliographies by topics / Medical knowledge engineering

Academic literature on the topic 'Medical knowledge engineering'

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Published: 10 March 2023

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Journal articles on the topic "Medical knowledge engineering"

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Paul, Norbert. "Deep models for medical knowledge engineering." Artificial Intelligence in Medicine 5, no. 6 (December 1993): 525–26. http://dx.doi.org/10.1016/0933-3657(93)90042-2.

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Lucas, Peter J. F. "Logic engineering in medicine." Knowledge Engineering Review 10, no. 2 (June 1995): 153–79. http://dx.doi.org/10.1017/s0269888900008134.

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AbstractThe safety-critical nature of the application of knowledge-based systems to the field of medicine requires the adoption of reliable engineering principles with a solid foundation for their construction. Logical languages with their inherent, precise notions of consistency, soundness and completeness provide such a foundation, thus promoting scrupulous engineering of medical knowledge. Moreover, logic techniques provide a powerful means for getting insight into the structure and meaning of medical knowledge used in medical problem solving. Unfortunately, logic is currently only used on a small scale for building practical medical knowledge-based systems. In this paper, the various approaches proposed in the literature are reviewed, and related to the various types of knowledge and problem solving employed in the medical field. The appropriateness of logic for building medical knowledge-based expert systems is further motivated.
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KUSHNIRUK, A., V. PATEL, and A. MARLEY. "Small worlds and medical expertise: implications for medical cognition and knowledge engineering." International Journal of Medical Informatics 49, no. 3 (May 1998): 255–71. http://dx.doi.org/10.1016/s1386-5056(98)00044-6.

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Walczak, Steven. "Managing personal medical knowledge: agent-based knowledge acquisition." International Journal of Technology Management 47, no. 1/2/3 (2009): 22. http://dx.doi.org/10.1504/ijtm.2009.024112.

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Ficoń, Krzysztof, Wojciech Sokołowski, and Marcin Zięcina. "Systems engineering – synergy of science, knowledge and applied technology." Scientific Journal of the Military University of Land Forces 206, no. 4 (December 15, 2022): 540–59. http://dx.doi.org/10.5604/01.3001.0016.1763.

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The following paper presents the theoretical foundations and selected practical applications of systems engineering. To begin with, the concept and subject of systems engineering is defined and embedded in the family of systems sciences. It also outlines the systems approach methodology applied in the systems engineering and the strong interdependencies that exist between systems theory and the practice of building systems applications. The matter of presenting selected categories of systems engineering, such as requirements engineering, environmental engineering, safety engineering, medical engineering, genetic engineering, management engineering, financial engineering, software engineering and social engineering was pivotal element of the paper. The paper has a form of a synthesis and an overview and contributes to further discussions within the framework of promoting a universal systems approach in the praxeological disciplines of the different categories of technical and non-technical, tangible and intangible, but always innovative and creative engineering.
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Fujikake, Mariko, Hideki Fujita, and Satoki P. Ninomija. "A method linking statistics and knowledge engineering for making medical consulting systems." Journal of Medical Systems 10, no. 3 (June 1986): 289–305. http://dx.doi.org/10.1007/bf00992824.

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Noor, Ahmed. "Re-Engineering Healthcare." Mechanical Engineering 129, no. 11 (November 1, 2007): 22–27. http://dx.doi.org/10.1115/1.2007-nov-1.

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This article reviews a system that is in need of repair in the United States, and engineers are uniquely equipped to help fix it. Although the expenditure per capita on healthcare in the United States is higher than in any other country, the current US healthcare system cannot be sustained, and major improvements are needed. Lives unnecessarily lost each year in the United States due to medical errors are estimated to be as high as 98,000 and injuries over a million. The healthcare system is currently facing many problems and challenges, including rapid changes in medical technology and practice, severe shortages in skilled healthcare workers, and an aging population with increased incidence of disease and disability. The cyber infrastructure will facilitate technology-based, distributed delivery of health services, as well as training and lifelong learning for healthcare workers. It can evolve into an electronic care continuum with pervasive access to global, accurate, and timely medical knowledge for individuals about their health needs in an era of rapid change and expanding knowledge.
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Wigertz, O., J. Persson, and H. Ahlfeldt. "Teaching Medical Informatics to Biomedical Engineering Students: Experiences over 15 Years." Methods of Information in Medicine 28, no. 04 (October 1989): 309–12. http://dx.doi.org/10.1055/s-0038-1636807.

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Abstract:The Departments of Biomedical Engineering and Medical Informatics at Linkoping University in Sweden were established in 1972-1973. The main purpose was to develop and offer courses in medicine, biomedical engineering and medical informatics to students in electrical engineering and computer science, for a specialization in biomedical engineering and medical informatics. The courses total about 400 hours of scheduled study in the subjects of basic cell biology, basic medicine (terminology, anatomy, physiology), biomedical engineering and medical informatics. Laboratory applications of medical computing are mainly taught in biomedical engineering courses, whereas clinical information systems, knowledge based decision support and computer science aspects are included within the medical informatics courses.
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Kaur, Aankita, and Mansaf Alam. "Role of Knowledge Engineering in the Development of a Hybrid Knowledge Based Medical Information System for Atrial Fibrillation." American Journal of Industrial and Business Management 03, no. 01 (2013): 36–41. http://dx.doi.org/10.4236/ajibm.2013.31005.

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Cheng, Binjie, Jin Zhang, Hong Liu, Meiling Cai, and Ying Wang. "Research on Medical Knowledge Graph for Stroke." Journal of Healthcare Engineering 2021 (March 24, 2021): 1–10. http://dx.doi.org/10.1155/2021/5531327.

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Knowledge graph can effectively analyze and construct the essential characteristics of data. At present, scholars have proposed many knowledge graph models from different perspectives, especially in the medical field, but there are still relatively few studies on stroke diseases using medical knowledge graphs. Therefore, this paper will build a medical knowledge graph model for stroke. Firstly, a stroke disease dictionary and an ontology database are built through the international standard medical term sets and semiautomatic extraction-based crowdsourcing website data. Secondly, the external data are linked to the nodes of the existing knowledge graph via the entity similarity measures and the knowledge representation is performed by the knowledge graph embedded model. Thirdly, the structure of the established knowledge graph is modified continuously through iterative updating. Finally, in the experimental part, the proposed stroke medical knowledge graph is applied to the real stroke data and the performance of the proposed knowledge graph approach on the series of Trans ∗ models is compared.
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Dissertations / Theses on the topic "Medical knowledge engineering"

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Graf, Franz. "Data and knowledge engineering for medical image and sensor data." Diss., lmu, 2012. http://nbn-resolving.de/urn:nbn:de:bvb:19-151051.

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Herrera-Hernandez, Maria Carolina. "Engineering of a Knowledge Management System for Relational Medical Diagnosis." Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4071.

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The increasingly high costs of health care in the U.S. have led the general public to search for different medical approaches. Since the 1990's, the use of Complementary and Alternative Medicine (CAM) has radically increased in the U.S. due to its approach to treat physical, mental, and emotional causes of illness. In 2009, the National Health Statistics reported the impact of CAM in the U.S. health care economy, with population expenditures of $14.8 billion out-of-pocket on natural Medicine and $12.4 billion out-of-pocket on visits to CAM providers as a complement to Western Medicine care. CAM interconnects human functions to reach a balanced state, whereas Western Medicine focuses on specialties and body systems. Both Western Medicine and CAM are unlimited sources of knowledge that follow different approaches but that have the common goal of improving patients' well-being. Identifying relationships between Alternative and Western Medicine can open a completely new approach for health care that can increase understanding of human medical conditions, and facilitate the development of new and more cost-effective treatments. However, the abundance and dissimilarity of CAM and Western Medicine data makes knowledge correlation and management an extremely challenging task. The objective of this research is to design the framework for a knowledge management system to organize, store, and manage the abundant data available for Western Medicine and CAM, and to establish key relationships between the two practices for an effective exploration of ideas and possible solutions for medical diagnosis. Three main challenges in the design of the proposed framework are addressed: data acquisition and modeling; data organization, storage and transfer; and information distribution for further generation and sharing of medical knowledge. A framework to relate the diagnosis process in Western Medicine and Traditional Chinese Medicine, as one of the various forms of CAM, is presented based on process-oriented analysis, hierarchical knowledge representation, relational database, and interactive interface for system utilization. The research is demonstrated using a case study on chronic prostatitis, and can be scalable to other medical conditions. The presented system for knowledge management is not intended to provide a definite solution for medical diagnosis, but to enable the exploration and discovery of knowledge for relational medical diagnosis. The results of this research will positively impact information distribution and knowledge generation via interactive medical knowledge systems, development of new skills for diagnosis and treatment, and a broader understanding of medical diseases and treatments.
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Kairouz, Joseph. "Patient data management system medical knowledge-base evaluation." Thesis, McGill University, 1996. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=24060.

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The purpose of this thesis is to evaluate the medical data management expert system at the Pediatric Intensive Care Unit of the Montreal Children's Hospital. The objective of this study is to provide a systematic method to evaluate and, progressively improve the knowledge embedded in the medical expert system.
Following a literature survey on evaluation techniques and architecture of existing expert systems, an overview of the Patient Data Management System hardware and software components is presented. The design of the Expert Monitoring System is elaborated. Following its installation in the intensive Care Unit, the performance of the Expert Monitoring System is evaluated, operating on real vital sign data and corrections were formulated. A progressive evaluation technique, new methodology for evaluating an expert system knowledge-base is proposed for subsequent corrections and evaluations of the Expert Monitoring System.
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Goldstein, Theodore C. "Tools for extracting actionable medical knowledge from genomic big data." Thesis, University of California, Santa Cruz, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3589324.

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Cancer is an ideal target for personal genomics-based medicine that uses high-throughput genome assays such as DNA sequencing, RNA sequencing, and expression analysis (collectively called omics); however, researchers and physicians are overwhelmed by the quantities of big data from these assays and cannot interpret this information accurately without specialized tools. To address this problem, I have created software methods and tools called OCCAM (OmiC data Cancer Analytic Model) and DIPSC (Differential Pathway Signature Correlation) for automatically extracting knowledge from this data and turning it into an actionable knowledge base called the activitome. An activitome signature measures a mutation's effect on the cellular molecular pathway. As well, activitome signatures can also be computed for clinical phenotypes. By comparing the vectors of activitome signatures of different mutations and clinical outcomes, intrinsic relationships between these events may be uncovered. OCCAM identifies activitome signatures that can be used to guide the development and application of therapies. DIPSC overcomes the confounding problem of correlating multiple activitome signatures from the same set of samples. In addition, to support the collection of this big data, I have developed MedBook, a federated distributed social network designed for a medical research and decision support system. OCCAM and DIPSC are two of the many apps that will operate inside of MedBook. MedBook extends the Galaxy system with a signature database, an end-user oriented application platform, a rich data medical knowledge-publishing model, and the Biomedical Evidence Graph (BMEG). The goal of MedBook is to improve the outcomes by learning from every patient.

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Graf, Franz [Verfasser], and Hans-Peter [Akademischer Betreuer] Kriegel. "Data and knowledge engineering for medical image and sensor data / Franz Graf. Betreuer: Hans-Peter Kriegel." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2012. http://d-nb.info/102873820X/34.

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Lundström, Claes. "Efficient Medical Volume Visualization : An Approach Based on Domain Knowledge." Doctoral thesis, Linköpings universitet, Visuell informationsteknologi och applikationer, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-9561.

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Direct Volume Rendering (DVR) is a visualization technique that has proved to be a very powerful tool in many scientific visualization applications. Diagnostic medical imaging is one domain where DVR could provide clear benefits in terms of unprecedented possibilities for analysis of complex cases and highly efficient work flow for certain routine examinations. The full potential of DVR in the clinical environment has not been reached, however, primarily due to limitations in conventional DVR methods and tools. This thesis presents methods addressing four major challenges for DVR in clinical use. The foundation of all methods is to incorporate the domain knowledge of the medical professional in the technical solutions. The first challenge is the very large data sets routinely produced in medical imaging today. To this end a multiresolution DVR pipeline is proposed, which dynamically prioritizes data according to the actual impact in the rendered image to be reviewed. Using this prioritization the system can reduce the data requirements throughout the pipeline and provide high performance and visual quality in any environment. Another problem addressed is how to achieve simple yet powerful interactive tissue classification in DVR. The methods presented define additional attributes that effectively captures readily available medical knowledge. The task of tissue detection is also important to solve in order to improve efficiency and consistency of diagnostic image review. Histogram-based techniques that exploit spatial relations in the data to achieve accurate and robust tissue detection are presented in this thesis. The final challenge is uncertainty visualization, which is very pertinent in clinical work for patient safety reasons. An animation method has been developed that automatically conveys feasible alternative renderings. The basis of this method is a probabilistic interpretation of the visualization parameters. Several clinically relevant evaluations of the developed techniques have been performed demonstrating their usefulness. Although there is a clear focus on DVR and medical imaging, most of the methods provide similar benefits also for other visualization techniques and application domains.
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Sidenvall, Adrian. "Knowledge sharing in and between agile software development teams using knowledge practices : An interpretive case study at a medium-sized medical IT company." Thesis, Linköpings universitet, Industriell ekonomi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138950.

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Agile methods for software development have become popular, especially since the agile manifesto was written in 2001. Many positive effects have been found in organizations using agile methods, but also several dangers. Communication and collaboration in teams is often mentioned as something that works well with the methods, but interactions between teams are often lacking. Since agile teams are cross-functional and focused on products rather than specializations, knowledge becomes spread out in the organization. Within teams, different members often have different deep knowledge, but instead have a lot of knowledge about their products in common. This allows them to discuss knowledge related to the product well, but limits their possibility to discuss advanced topics and experiences regarding their deep knowledge or specialization within their team. These issues are important to consider when applying agile methods in organizations, and the research about the issues is quite thin.   In this research, I have taken an interpretive approach and carried out a case study at the development department of a medium-sized IT company providing large software systems for the healthcare industry, for which I have used the pseudonym MedTech. Three different teams have been studied through interviews with all members as well as observations of agile practices like daily meetings. Further, I have studied three different knowledge practices that MedTech uses to complement the creation and sharing of knowledge that happens in teams. These three complementary knowledge practices had different forms and handled knowledge in different ways. One was closely related to what literature often calls communities of practice, which are groups where members share an interest and interact to deepen their knowledge. In this practice at MedTech, meetings were used to discuss experiences and knowledge about topics within specific areas. Another was more focused on one-way communication through presentations and reading tips, spreading more basic knowledge to a wider audience. The third complementary knowledge practice let employees use 12 work hours every sixth week to do whatever they wanted that related to their knowledge, allowing them to e.g. explore new technologies and be creative or simply read up on some interesting topic.   My results show that agile teams support some sharing and creation of knowledge, especially through having members work closely to each other and share experiences, and through practising their skills in daily work, with help from each other when necessary. Like other research has shown, there was however a lack of practices for interactions between teams in the agile methods. Such interactions were crucial since I found teams to be comparable to theories about communities of knowing, where teams create strong perspectives, the sharing of which is important for utilization and creation of knowledge. The complementary knowledge practice that related to communities of practice was shown to be good for connecting employees with similar specializations, who would normally be separated in different teams. This allowed for creation and sharing of knowledge as individuals needed to explain their experiences and could combine knowledge from different members of the community. The other two complementary knowledge practices were shown to be good for increasing motivation to create and share knowledge, and showing that the organization valued the knowledge of individuals.
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Smith, Michael William. "Utilizing Control in Emergency Medical Services: Expertise in Paramedics." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1291139651.

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Chueh, Henry C. "Integration of expert knowledge into computer-controlled databases in the medical domain : HEMAVID, a case study." Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/29202.

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Thesis (M.S.)--Harvard University--Massachusetts Institute of Technology Division of Health Sciences and Technology, Program in Medical Engineering and Medical Physics, 1989.
Includes bibliographical references (leaves [165]-[172]).
by Henry C. Chueh.
M.S.
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Essafi, Salma. "3D Knowledge-based Segmentation Using Sparse Hierarchical Models : contribution and Applications in Medical Imaging." Phd thesis, Ecole Centrale Paris, 2010. http://tel.archives-ouvertes.fr/tel-00534805.

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CETTE thèse est consacrée à la conception d'un système d'aide au diagnostic dédiéau muscle squelettique humain. Au cours du premier volet de ce manuscrit nousproposons une nouvelle représentation basée sur les modèles parcimonieux dans le cadrede la segmentation d'Images de Résonances Magnétiques (IRM) T1 du muscle squelettiquedu mollet. Notre méthode Sparse Shape Model/ Modèle de Formes Parcimonieux(MFP), apprend un modèle statistique de formes et de textures locales annoté et réussità en tirer une représentation réduite afin de reconstruire le mécanisme musculaire sur unexemple test. Dans la seconde partie du manuscrit, nous présentons une approche baséesur des ondelettes de diffusion pour la segmentation du muscle squelettique. Contrairementaux méthodes de l'état de l'art, notre approche au cours de la phase d'apprentissagepermet à optimiser les coefficients des ondelettes, ainsi que leur nombres et leur positions.Le modèle prend en charge aussi bien les hiérarchies dans l'espace de recherche,que l'encodage des dépendances géométriques complexes et photométriques de la structured'intérêt. Notre modélisation offre ainsi l'avantage de traiter des topologies arbitraires.L'évaluation expérimentale a été effectué sur un ensemble de mollets acquisespar un scanner IRM, ainsi qu'un ensemble d'images tomodensitométriques du ventriculegauche.
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Books on the topic "Medical knowledge engineering"

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Camargo, Jorge Enrique Caviedas. Mekeas: a medical knowledge engineering assistant. Ann Arbor, Mi: University Microfilms International, 1987.

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T, Keravnou E., ed. Deep models for medical knowledge engineering. Amsterdam: Elsevier, 1992.

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Warner, Homer R. Knowledge engineering in health informatics. New York: Springer, 1997.

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1947-, Sorenson Dean K., and Bouhaddou Omar, eds. Knowledge engineering in health informatics. New York: Springer, 1997.

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From patient data to medical knowledge: The principles and practice of health informatics. Malden, Mass: Blackwell Pub., 2006.

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1948-, Talmon Jan L., Fox J, Rijksuniversiteit Limburg. Dept. of Medical Informatics., Commission of the European Communities., and Commission of the European Communities. Medical and Health Research Programme., eds. Knowledge based systems in medicine: Methods, applications, and evaluation : proceedings of the Workshop "System Engineering in Medicine," Maastricht, March 16-18, 1989. Berlin: Springer-Verlag, 1991.

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Valérie, Burri Regula, and Dumit Joseph, eds. Biomedicine as culture: Instrumental practices, technoscientific knowledge, and new modes of life. New York: Routledge, 2007.

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Pham, Tuan D. Knowledge-Based Systems in Biomedicine and Computational Life Science. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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J, Hamilton Howard, ed. Knowledge discovery and measures of interest. Boston: Kluwer Academic Publishers, 2001.

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Hilderman, Robert J. Knowledge discovery and measures of interest. Boston: Kluwer Academic, 2001.

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Book chapters on the topic "Medical knowledge engineering"

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von Michalik, Krzysztof, Mila Kwiatkowska, and Krzysztof Kielan. "Application of Knowledge-Engineering Methods in Medical Knowledge Management." In Fuzziness and Medicine: Philosophical Reflections and Application Systems in Health Care, 205–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36527-0_14.

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Komkhao, Maytiyanin, Jie Lu, and Lichen Zhang. "Determining Pattern Similarity in a Medical Recommender System." In Data and Knowledge Engineering, 103–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34679-8_11.

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Haag, U., R. Baud, J. R. Scherrer, and C. O. Kohler. "Interfacing PROLOG and SQL for Medical Knowledge Engineering Development." In Medical Informatics Europe ’90, 249–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-51659-7_48.

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Blesik, Till, and Markus Bick. "Adoption Factors for Crowdsourcing Based Medical Information Platforms." In Knowledge Science, Engineering and Management, 172–84. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47650-6_14.

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Zhai, Yong-Hua, Ying Zhao, and Rui-Mei Wang. "Knowledge Management of Medical Decision Based on Evidence." In Lecture Notes in Electrical Engineering, 615–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40630-0_78.

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Qian, Danmin, Yuanpeng Zhang, Jiancheng Dong, and Li Wang. "Mapping Knowledge Domain Analysis of Medical Informatics Education." In Lecture Notes in Electrical Engineering, 2209–13. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7618-0_269.

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Lei, Kai, Kaiqi Yuan, Qiang Zhang, and Ying Shen. "MedSim: A Novel Semantic Similarity Measure in Bio-medical Knowledge Graphs." In Knowledge Science, Engineering and Management, 479–90. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99365-2_43.

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Zhang, Huiru, Guangshun Li, Yue Zhang, Keke Gai, and Meikang Qiu. "Blockchain-Based Privacy-Preserving Medical Data Sharing Scheme Using Federated Learning." In Knowledge Science, Engineering and Management, 634–46. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82153-1_52.

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Wang, Haiqiang, Xuyuan Dong, Zheng Luo, Junyou Zhu, Peican Zhu, and Chao Gao. "Medication Combination Prediction via Attention Neural Networks with Prior Medical Knowledge." In Knowledge Science, Engineering and Management, 311–22. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-82153-1_26.

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Ma, Zhien, and Jianquan Li. "Basic Knowledge and Developing Tendencies in Epidemic Dynamics." In Biological and Medical Physics, Biomedical Engineering, 5–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-34426-1_2.

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Conference papers on the topic "Medical knowledge engineering"

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Taweel, Adel. "Session details: Bio-medical knowledge representation & engineering." In CIKM '11: International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2011. http://dx.doi.org/10.1145/3247996.

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Min, Hua. "Session details: Bio-medical knowledge representation & engineering." In CIKM'12: 21st ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2012. http://dx.doi.org/10.1145/3251599.

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van Daalen, Cornelia. "Evaluating medical knowledge based systems." In 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.5761292.

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Van Daalen. "Evaluating Medical Knowledge Based Systems." In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 1992. http://dx.doi.org/10.1109/iembs.1992.594634.

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Tokosumi, Akifumi, Naoko Matsumoto, and Hajime Murai. "Medical Ontologies as a Knowledge Repository." In 2007 IEEE/ICME International Conference on Complex Medical Engineering. IEEE, 2007. http://dx.doi.org/10.1109/iccme.2007.4381782.

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Firdaus, Oktri Mohammad, Kadarsah Suryadi, Rajesri Govindaraju, and T. M. A. Ari Samadhi. "Medical knowledge sharing guideline: A conceptual model." In Knowledge Engineering 2011) - Conference postponed to 2012. IEEE, 2012. http://dx.doi.org/10.1109/ictke.2012.6152408.

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Qian, JianZhong. "Knowledge-based topographic feature extraction in medical images." In Optical Engineering Midwest '95. SPIE, 1995. http://dx.doi.org/10.1117/12.216785.

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Jang, Hyeju, Sa Kwang Song, and Sung Hyon Myaeng. "Semantic Tagging for Medical Knowledge Tracking." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.260154.

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Jang, Hyeju, Sa Kwang Song, and Sung Hyon Myaeng. "Semantic Tagging for Medical Knowledge Tracking." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4398889.

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Jaisook, Phanchaporn, and Wichian Premchaiswadi. "Time performance analysis of medical treatment processes by using disco." In 2015 13th International Conference on ICT and Knowledge Engineering (ICT & Knowledge Engineering 2015). IEEE, 2015. http://dx.doi.org/10.1109/ictke.2015.7368480.

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Reports on the topic "Medical knowledge engineering"

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Chen, Xianglei, and Susan Rotermund. Entering the Skilled Technical Workforce After College. RTI Press, April 2020. http://dx.doi.org/10.3768/rtipress.2020.rb.0024.2004.

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This research brief uses nationally representative data from the 2012/17 Beginning Postsecondary Students Longitudinal Study (BPS:12/17) to examine post-college transitions of US undergraduates into the skilled technical workforce (STW), defined here as workers in a collection of occupations that require significant levels of science, technology, engineering, and mathematics (STEM) knowledge but not necessarily a bachelor’s degree for entry. Thus far, empirical research on the STW has been limited by a dearth of data; however, based on newly available data from BPS:12/17, the findings in this report indicate that STW employment provides workers with above-median salaries, more equitable wages, a variety of benefits, and clear career paths. STW jobs attract diverse populations, especially those from underrepresented groups (e.g., Hispanics, individuals from low-income backgrounds, and those whose parents do not have college education). US community colleges and sub-baccalaureate programs play a large role in developing the STW.
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2

Fridman, Eyal, and Eran Pichersky. Tomato Natural Insecticides: Elucidation of the Complex Pathway of Methylketone Biosynthesis. United States Department of Agriculture, December 2009. http://dx.doi.org/10.32747/2009.7696543.bard.

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Plant species synthesize a multitude of specialized compounds 10 help ward off pests. and these in turn may well serve as an alternative to synthetic pesticides to reduce environmental damage and health risks to humans. The general goal of this research was to perform a genetic and biochemical dissection of the natural-insecticides methylketone pathway that is specific to the glandular trichomes of the wild species of tomato, Solanumhabrochaites f. glabratum (accession PI126449). Previous study conducted by us have demonstrated that these compounds are synthesized de novo as a derivate pathway of the fatty acid biosynthesis, and that a key enzyme. designated MethylketoneSynthase 1 (MKS 1). catalyzes conversion of the intermediate B-ketoacyl- ACPs to the corresponding Cn-1 methylketones. The approach taken in this proposed project was to use an interspecific F2 population. derived from the cross between the cultivated lV182 and the wild species PIl26449. for three objectives: (i) Analyze the association between allelic status of candidate genes from the fatty acid biosynthesis pathway with the methylketone content in the leaves (ii) Perform bulk segregant analysis of genetic markers along the tomato genome for identifying genomic regions that harbor QTLs for 2TD content (iii) Apply differential gene expression analysis using the isolated glands of bulk segregant for identifying new genes that are involved in the pathway. The genetic mapping in the interspecific F2 population included app. 60 genetic markers, including the candidate genes from the FAS pathway and SSR markers spread evenly across the genome. This initial; screening identified 5 loci associated with MK content including the candidate genes MKS1, ACC and MaCoA:ACP trans. Interesting observation in this genetic analysis was the connection between shape and content of the glands, i.e. the globularity of the four cells, typical to the wild species. was associated with increased MK in the segregating population. In the next step of the research transcriptomic analysis of trichomes from high- and 10w-MK plants was conducted. This analysis identified a new gene, Methy1ketone synthase 2 (MKS2), whose protein product share sequence similarity to the thioesterase super family of hot-dog enzymes. Genetic analysis in the segregating population confirmed its association with MK content, as well as its overexpression in E. coli that led to formation of MK in the media. There are several conclusions drawn from this research project: (i) the genetic control of MK accumulation in the trichomes is composed of biochemical components in the FAS pathway and its vicinity (MKS 1 and MKS2). as well as genetic factors that mediate the morphology of these specialized cells. (ii) the biochemical pathway is now realized different from what was hypothesized before with MKS2 working upstream to I\1KS 1 and serves as the interface between primary (fatty acids) and secondary (MK) metabolism. We are currently testing the possible physical interactions between these two proteins in vitro after the genetic analysis showed clear epistatic interactions. (iii) the regulation of the pathway that lead to specialized metabolism in the wild species is largely mediated by transcription and one of the achievements of this project is that we were able to isolate and verify the specificity of the MKS1 promoter to the trichomes which allows manipulation of the pathways in these cells (currently in progress). The scientific implications of this research project is the advancement in our knowledge of hitherto unknown biochemical pathway in plants and new leads for studying a new family in plants (hot dog thioesterase). The agricultural and biotechnological implication are : (i) generation of new genetic markers that could assist in importing this pathway to cultivated tomato hence enhancing its natural resistance to insecticides, (ii) the discovery of MKS2 adds a new gene for genetic engineering of plants for making new fatty acid derived compounds. This could be assisted with the use of the isolated and verified MKS1 promoter. The results of this research were summarized to a manuscript that was published in Plant Physiology (cover paper). to a chapter in a proceeding book. and one patent was submitted in the US.
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