Learn · Machine Learning for Healthcare

Lecture 5 of 25Lecture Videos1 h 21 min

Lecture 5: Risk Stratification, Part 2

Prof. Peter Szolovits and Prof. David Sontag · Massachusetts Institute of Technology

At MIT OpenCourseWare Transcript

Credits and licence

From
Machine Learning for Healthcare, Massachusetts Institute of Technology (at MIT OpenCourseWare)
Licence
CC BY-NC-SA 4.0, as MIT OpenCourseWare states it. Non-commercial use only.
Attribution
Prof. Peter Szolovits, Prof. David Sontag. Machine Learning for Healthcare. Spring 2019. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu/. License: Creative Commons BY-NC-SA.
Who can watch
Teens profiles and older. How courses are placed

All the lectures

  1. Lecture 1: What Makes Healthcare Unique? 1 h 11 min · Video
  2. Lecture 2: Overview of Clinical Care 1 h 21 min · Video
  3. Lecture 3: Deep Dive Into Clinical Data 1 h 24 min · Video
  4. Lecture 4: Risk Stratification, Part 1 1 h 13 min · Video
  5. Lecture 5: Risk Stratification, Part 2 1 h 21 min · Video
  6. Lecture 6: Physiological Time-Series 1 h 21 min · Video
  7. Lecture 7: Natural Language Processing (NLP), Part 1 1 h 16 min · Video
  8. Lecture 8: Natural Language Processing (NLP), Part 2 1 h 24 min · Video
  9. Lecture 9: Translating Technology Into the Clinic 1 h 23 min · Video
  10. Lecture 10: Application of Machine Learning to Cardiac Imaging 1 h 22 min · Video
  11. Lecture 11: Differential Diagnosis 1 h 21 min · Video
  12. Lecture 12: Machine Learning for Pathology 56 min · Video
  13. Lecture 13: Machine Learning for Mammography 42 min · Video
  14. Lecture 14: Causal Inference, Part 1 1 h 19 min · Video
  15. Lecture 15: Causal Inference, Part 2 1 h 3 min · Video
  16. Lecture 16: Reinforcement Learning, Part 1 1 h 18 min · Video
  17. Lecture 17: Reinforcement Learning, Part 2 56 min · Video
  18. Lecture 18: Disease Progression Modeling and Subtyping, Part 1 1 h 22 min · Video
  19. Lecture 19: Disease Progression Modeling and Subtyping, Part 2 1 h 13 min · Video
  20. Lecture 20: Precision Medicine 1 h 25 min · Video
  21. Lecture 21: Automating Clinical Work Flows 1 h 21 min · Video
  22. Lecture 22: Regulation of Machine Learning / Artificial Intelligence in the US 1 h 22 min · Video
  23. Lecture 23: Fairness 1 h 18 min · Video
  24. Lecture 24: Robustness to Dataset Shift 1 h 16 min · Video
  25. Lecture 25: Interpretability 1 h 19 min · Video