Learn · Machine Learning for Healthcare
Lecture 16 of 25Lecture Videos1 h 18 min
Lecture 16: Reinforcement Learning, Part 1
Prof. Peter Szolovits and Prof. David Sontag · Massachusetts Institute of Technology
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
- Lecture 1: What Makes Healthcare Unique?
- Lecture 2: Overview of Clinical Care
- Lecture 3: Deep Dive Into Clinical Data
- Lecture 4: Risk Stratification, Part 1
- Lecture 5: Risk Stratification, Part 2
- Lecture 6: Physiological Time-Series
- Lecture 7: Natural Language Processing (NLP), Part 1
- Lecture 8: Natural Language Processing (NLP), Part 2
- Lecture 9: Translating Technology Into the Clinic
- Lecture 10: Application of Machine Learning to Cardiac Imaging
- Lecture 11: Differential Diagnosis
- Lecture 12: Machine Learning for Pathology
- Lecture 13: Machine Learning for Mammography
- Lecture 14: Causal Inference, Part 1
- Lecture 15: Causal Inference, Part 2
- Lecture 16: Reinforcement Learning, Part 1
- Lecture 17: Reinforcement Learning, Part 2
- Lecture 18: Disease Progression Modeling and Subtyping, Part 1
- Lecture 19: Disease Progression Modeling and Subtyping, Part 2
- Lecture 20: Precision Medicine
- Lecture 21: Automating Clinical Work Flows
- Lecture 22: Regulation of Machine Learning / Artificial Intelligence in the US
- Lecture 23: Fairness
- Lecture 24: Robustness to Dataset Shift
- Lecture 25: Interpretability