Machine Learning for Healthcare

Calendar

Ses #	Topics	Key Dates
1	Introduction: What Makes Healthcare Unique?	Problem Set 0 Out
2	Overview of Clinical Care
3	Deep Dive into Clinical Data	Reading Questions Problem Set 0 Due Problem Set 1 Out
4	Risk Stratification, Part 1 Discussant: Leonard D’Avolio	Reading Questions
5	Risk Stratification, Part 2	Reading Questions Problem Set 1 Due
6	Physiological Time-Series	Reading Questions Problem Set 2 Out
7	Natural Language Processing (NLP), Part 1 Discussant: Katherine Liao	Reading Questions
8	Natural Language Processing (NLP), Part 2	Problem Set 2 Due Problem Set 3 Out
9	Translating Technology into the Clinic Discussant: Adam Wright
10	Machine Learning for Cardiology Guest Lecture: Rahul Deo	Reading Questions Problem Set 3 Due Problem Set 4 Out
11	Machine Learning for Differential Diagnosis	Reading Questions
12	Machine Learning for Pathology Guest Lecture: Andy Beck	Reading Questions Problem Set 4 Due
13	Machine Learning for Mammography  Guest Lecture: Connie Lehman, Adam Yala	Reading Questions Project Proposals Due
14	Causal Inference, Part 1	Reading Questions Problem Set 5 Out
15	Causal Inference, Part 2	Midsemester Feedback
16	Reinforcement Learning, Part 1 Guest Lecture: Fredrik Johansson	Reading Questions
17	Reinforcement Learning, Part 2 Guest Lecture: Barbra Dickerman Evaluating Dynamic Treatment Strategies	Reading Questions Problem Set 5 Due
18	Disease Progression & Subtyping, Part 1	Problem Set 6 Out
19	Disease Progression & Subtyping, Part 2
20	Precision Medicine	Problem Set 6 Due
21	Automating Clinical Workflows
22	Regulation of ML/AI in the US Guest Lecture: Andy Coravos Human Subjects Research Guest Lecture: Mark Shervey	Reading Questions
23	Fairness
24	Robustness to Dataset Shift	Project Presentations
25	Interpretability	Project Reports Due