Curriculum
1 Section
25 Lessons
Lifetime
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Lessons
25
1.0
1. What Makes Healthcare Unique?
1.1
2. Overview of Clinical Care
1.2
3. Deep Dive Into Clinical Data
1.3
4. Risk Stratification Part 1
1.4
5. Risk Stratification Part 2
1.5
6. Physiological Time-Series
1.6
7. Natural Language Processing (NLP) Part 1
1.7
8. Natural Language Processing (NLP) Part 2
1.8
9. Translating Technology Into the Clinic
1.9
10. Application of Machine Learning to Cardiac Imaging
1.10
11. Differential Diagnosis
1.11
12. Machine Learning for Pathology
1.12
13. Machine Learning for Mammography
1.13
14. Causal Inference Part 1
1.14
15. Causal Inference Part 2
1.15
16. Reinforcement Learning Part 1
1.16
17. Reinforcement Learning Part 2
1.17
18. Disease Progression Modeling and Subtyping Part 1
1.18
19. Disease Progression Modeling and Subtyping Part 2
1.19
20. Precision Medicine
1.20
21. Automating Clinical Work Flows
1.21
22. Regulation of Machine Learning / Artificial Intelligence in the US
1.22
23. Fairness
1.23
24. Robustness to Dataset Shift
1.24
25. Interpretability
Machine Learning for Healthcare
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