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Wondering how it possible to correlate clinical outcomes with genomic data? Or what are the risks that genomic data pose to personal privacy? Enrol the [course_title] course and explore the computational needs of clinical medicine reviews systems and approaches that are used to support those needs.
In the course, you will learn the relationship between clinical data and gene and protein measurements. Other areas covered in the course are the nature of clinical data, architecture and design of healthcare information systems, privacy and security issues, medical expert systems, and introduction to bioinformatics.
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Course Credit: MIT
Course Curriculum
| L-1 Nature of clinical data (Peter Szolovits) | 00:40:00 | ||
| L-2 Standards (Peter Szolovits) Part 1 | 00:15:00 | ||
| L-3 Standards (Peter Szolovits) Part 2 | 01:05:00 | ||
| L-4 Data in narrative text (Peter Szolovits) | 00:30:00 | ||
| L-5 Building models (Peter Szolovits) | 00:30:00 | ||
| L-6 Decision support via probabilities and utilities (Peter Szolovits) | 00:35:00 | ||
| L-7 Decision support via expert systems (Peter Szolovits) | 00:35:00 | ||
| L-8 Modeling with bayesian networks (Peter Szolovits) | 00:15:00 | ||
| L-9 Patient monitoring and intensive care (Leo Celi) | 00:25:00 | ||
| L-10 HIT in the developing world (Hamish Fraser) | 00:25:00 | ||
| L-11 Learning bayesian networks (Peter Szolovits) | 00:10:00 | ||
| L-12 Patient data privacy (Peter Szolovits and Chris Cassa) | 00:15:00 | ||
| L-13 Computer science challenges from health care (Peter Szolovits) | 00:20:00 | ||
| Assessment | |||
| Submit Your Assignment | 00:00:00 | ||
| Certification | 00:00:00 | ||
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