Machine Learning for Healthcare

Lecture Notes

Ses #	Lecture Slides	Lecture Notes
1	Lecture 1: Introduction: What Makes Healthcare Unique? slides (PDF - 2.4MB)	Lecture 1 Notes (PDF)
2	Lecture 2: Overview of Clinical Care slides (PDF - 2.6MB)	Lecture 2 Notes (PDF)
3	Lecture 3: Deep Dive into Clinical Data slides (PDF - 2.1MB)	Lecture 3 Notes (PDF - 1.5MB)
4	Lecture 4: Risk Stratification, Part 1 slides (PDF - 1.2MB)	Lecture 4 Notes (PDF)
5	Lecture 5: Risk Stratification, Part 2 slides (PDF - 1.9MB)	Lecture 5 Notes (PDF)
6	Lecture 6: Physiological Time-Series slides (PDF - 1.4MB)	Lecture 6 Notes (PDF)
7	Lecture 7: Natural Language Processing (NLP), Part 1 slides (PDF - 1MB)	Lecture 7 Notes (PDF)
8	Lecture 8: Natural Language Processing (NLP), Part 2 slides (PDF - 2.0MB)	Lecture 8 Notes (PDF)
9	Lecture 9: Translating Technology into the Clinic slides (PDF)	Lecture 9 Notes (PDF)
10	Lecture 10: Machine Learning for Cardiology slides (PDF - 3.9MB)	Lecture 10 Notes (PDF - 1.3MB)
11	Lecture 11: Machine Learning for Differential Diagnosis slides (PDF - 1.9MB)	Lecture 11 Notes (PDF)
12	Lecture 12: Machine Learning for Pathology slides (PDF - 6.8MB)	Lecture 12 Notes (PDF)
13	Lecture 13: Machine Learning for Mammography slides (PDF - 2.2MB)	Lecture 13 Notes (PDF)
14	Lecture 14: Causal Inference, Part 1 slides (PDF - 2MB)	Lecture 14 Notes (PDF)
15	Lecture 15: Causal Inference, Part 2 slides (PDF)	Lecture 15 Notes (PDF)
16	Lecture 16: Reinforcement Learning slides (PDF)	Lecture 16 Notes (PDF)
17	Lecture 17: Evaluating Dynamic Treatment Strategies slides (PDF)	Lecture 17 Notes (PDF)
18	Lecture 18: Disease Progression & Subtyping, Part 1 slides (PDF)	Lecture 18 Notes (PDF)
19	Lecture 19: Disease Progression & Subtyping, Part 2 slides (PDF - 2.5MB)	Lecture 19 Notes (PDF)
20	Lecture 20: Precision Medicine slides (PDF - 1.6MB)	Lecture 20 Notes (PDF)
21	Lecture 21: Automating Clinical Workflows slides (PDF - 1.6MB)	Lecture 21 Notes (PDF)
22	Lecture 22.1: Regulation of ML/AI in the US slides (PDF - 1.4MB) Lecture 22.2: Human Subjects Research slides (PDF)	Lecture 22 Notes (PDF)
23	Lecture 23: Fairness slides (PDF - 1.5MB)	No provided notes
24	Lecture 24: Robustness to Dataset Shift slides (PDF - 2.2MB)	Lecture 24 Notes (PDF)
25	Lecture 25: Interpretability slides (PDF - 3.2MB)	No provided notes