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HST.951J Medical Decision Support (MIT) HST.951J Medical Decision Support (MIT)

Description

This course presents the main concepts of decision analysis, artificial intelligence, and predictive model construction and evaluation in the specific context of medical applications. The advantages and disadvantages of using these methods in real-world systems are emphasized, while students gain hands-on experience with application specific methods. The technical focus of the course includes decision analysis, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks), and techniques to evaluate the performance of such systems. This course presents the main concepts of decision analysis, artificial intelligence, and predictive model construction and evaluation in the specific context of medical applications. The advantages and disadvantages of using these methods in real-world systems are emphasized, while students gain hands-on experience with application specific methods. The technical focus of the course includes decision analysis, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks), and techniques to evaluate the performance of such systems.

Subjects

HST.951 | HST.951 | 6.873 | 6.873 | decision analysis | decision analysis | artificial intelligence | artificial intelligence | predictive model construction | predictive model construction | evaluation | evaluation | medical software | medical software | decision support | decision support | knowledge-based systems | knowledge-based systems | learning systems | learning systems | logistic regression | logistic regression | classification trees | classification trees | neural networks | neural networks | rough sets | rough sets | computer-based diagnosis | computer-based diagnosis | planning monitoring | planning monitoring | therapeutic interventions | therapeutic interventions | machine learning methods | machine learning methods

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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HST.951J Medical Decision Support (MIT) HST.951J Medical Decision Support (MIT)

Description

This course presents the main concepts of decision analysis, artificial intelligence and predictive model construction and evaluation in the specific context of medical applications. It emphasizes the advantages and disadvantages of using these methods in real-world systems and provides hands-on experience. Its technical focus is on decision support, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks, rough sets), and techniques to evaluate the performance of such systems. It reviews computer-based diagnosis, planning and monitoring of therapeutic interventions. It also discusses implemented medical applications and the software tools used in their construction. Students produce a final project usin This course presents the main concepts of decision analysis, artificial intelligence and predictive model construction and evaluation in the specific context of medical applications. It emphasizes the advantages and disadvantages of using these methods in real-world systems and provides hands-on experience. Its technical focus is on decision support, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks, rough sets), and techniques to evaluate the performance of such systems. It reviews computer-based diagnosis, planning and monitoring of therapeutic interventions. It also discusses implemented medical applications and the software tools used in their construction. Students produce a final project usin

Subjects

decision analysis | decision analysis | artificial intelligence | artificial intelligence | predictive model construction | predictive model construction | evaluation | evaluation | medical software | medical software | decision support | decision support | knowledge-based systems | knowledge-based systems | learning systems | learning systems | logistic regression | logistic regression | classification trees | classification trees | neural networks | neural networks | rough sets | rough sets | computer-based diagnosis | computer-based diagnosis | planning monitoring | planning monitoring | therapeutic interventions | therapeutic interventions | machine learning methods | machine learning methods | HST.951 | HST.951 | 6.873 | 6.873

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

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http://ocw.mit.edu/rss/all/mit-allcourses-HST.xml

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HST.951J Medical Decision Support (MIT)

Description

This course presents the main concepts of decision analysis, artificial intelligence and predictive model construction and evaluation in the specific context of medical applications. It emphasizes the advantages and disadvantages of using these methods in real-world systems and provides hands-on experience. Its technical focus is on decision support, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks, rough sets), and techniques to evaluate the performance of such systems. It reviews computer-based diagnosis, planning and monitoring of therapeutic interventions. It also discusses implemented medical applications and the software tools used in their construction. Students produce a final project usin

Subjects

decision analysis | artificial intelligence | predictive model construction | evaluation | medical software | decision support | knowledge-based systems | learning systems | logistic regression | classification trees | neural networks | rough sets | computer-based diagnosis | planning monitoring | therapeutic interventions | machine learning methods | HST.951 | 6.873

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

Site sourced from

https://ocw.mit.edu/rss/all/mit-allcourses.xml

Attribution

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HST.951J Medical Decision Support (MIT)

Description

This course presents the main concepts of decision analysis, artificial intelligence and predictive model construction and evaluation in the specific context of medical applications. It emphasizes the advantages and disadvantages of using these methods in real-world systems and provides hands-on experience. Its technical focus is on decision support, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks, rough sets), and techniques to evaluate the performance of such systems. It reviews computer-based diagnosis, planning and monitoring of therapeutic interventions. It also discusses implemented medical applications and the software tools used in their construction. Students produce a final project usin

Subjects

decision analysis | artificial intelligence | predictive model construction | evaluation | medical software | decision support | knowledge-based systems | learning systems | logistic regression | classification trees | neural networks | rough sets | computer-based diagnosis | planning monitoring | therapeutic interventions | machine learning methods | HST.951 | 6.873

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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https://ocw.mit.edu/rss/all/mit-allsimplifiedchinesecourses.xml

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HST.951J Medical Decision Support (MIT)

Description

This course presents the main concepts of decision analysis, artificial intelligence, and predictive model construction and evaluation in the specific context of medical applications. The advantages and disadvantages of using these methods in real-world systems are emphasized, while students gain hands-on experience with application specific methods. The technical focus of the course includes decision analysis, knowledge-based systems (qualitative and quantitative), learning systems (including logistic regression, classification trees, neural networks), and techniques to evaluate the performance of such systems.

Subjects

HST.951 | 6.873 | decision analysis | artificial intelligence | predictive model construction | evaluation | medical software | decision support | knowledge-based systems | learning systems | logistic regression | classification trees | neural networks | rough sets | computer-based diagnosis | planning monitoring | therapeutic interventions | machine learning methods

License

Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see https://ocw.mit.edu/terms/index.htm

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https://ocw.mit.edu/rss/all/mit-alllifesciencescourses.xml

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