| 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 |