Course Syllabus

BIOMEDIN 205: Precision Medicine and Big Data

Fall 2019

Course Description

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.

 

Course Personnel

  • Instructor: Daniel Rubin, P.h.D, rubin (at) stanford.edu
  • Teaching Assistant: Alice Yu, ayu1 (at) stanford.edu

 

Course Logistics

  • 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

Speakers Schedule

Date Presenter Department Title Room
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
11/27 No Class
12/04 Jared Dunnmon Weak Supervision in Medical Machine Learning: Concepts, Techniques, Applications, and Caveats LKSC101

 

 

 

 

 

 

Course Summary:

Date Details