BIOMEDIN 205: Precision Medicine and Big Data
Primarily for M.D. students; open to other graduate students. This course provides an overview of how to leverage large amounts of clinical, molecular, and imaging data within hospitals and in cyberspace--big data--to practice medicine more effectively. Lectures by physicians, researchers, and industry leaders survey how the major methods of informatics can help physicians leverage big data to profile disease, to personalize treatment to patients, to predict treatment response, to discover new knowledge, and to challenge established medical dogma and the current paradigm of clinical decision-making based solely on
published knowledge and individual physician experience. May be repeated for credit.
Prerequisite: Background in biomedicine. Background in computer science can be helpful but not required.
- Instructor: Daniel Rubin, P.h.D, rubin (at) stanford.edu
- Teaching Assistant: Alice Yu, ayu1 (at) stanford.edu
- Location: LKSC (Alternating room for each class listed down below)
- Time: Wednesdays, 12:30 - 1:20 PM
- Grading: Pass/Fail, 1 Unit. May be repeated.
- To receive credit, students must attend every class or complete the make-up assignment (questions on the lecture) for the days missed.
- Make-up assignments for missed classes will be posted on Canvas under Files/Lecture Questions the afternoon following the lecture and due before the end of the quarter. Please email answers to the TA
- Class readings are available under Files/Readings/Professor_Name. Please read before each class to understand the background of the lecture.
- Lecture recordings under Lecture Media/
- Lunch is provided at 12:00 PM for all registered students
|9/25||Daniel Rubin||DBDS, Radiology, Medicine||Artificial Intelligence Approaches to Medical Imaging||MSOBx303|
|10/02||James Zou||DBDS||Transparent Machine learning for Genomics and Biomedicine||LKSC120|
|10/09||Trevor Hastie||Statistics, DBDS||Statistical Learning with Sparsity||LKSC130|
|10/16||Euan Ashley||Medicine, Genetics, DBDS||The Science of Precision Medicine||LKSC130|
|10/23||Jennifer Frankovich||Pediatrics||Data at the Bedside: using informatics to improve clinical care.||LKSC101|
|10/30||Aaron Newman||DBDS||Data Science for Precision Cancer Medicine||LKSC130|
|11/06||Jonathan Chen||Medicine||Data-Mining Electronic Medical Records for Clinical Decision Support - Discovering and Distributing the Latent Knowledge Embedded in Clinical Data||LKSC130|
|11/13||Dennis Wall||Pediatrics, DBDS||AI technologies for pediatric health||LKSC120|
|11/20||Serena Yeung||DBDS||Computer Vision Methods for Automated Observational Study of Hospital Care Processes||LKSC130|
|12/04||Jared Dunnmon||Weak Supervision in Medical Machine Learning: Concepts, Techniques, Applications, and Caveats||LKSC101|
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