MIT 6.S897 Machine Learning for Healthcare, Spring 2019 (English)

   Friday, December 06, 2024   

Starting a new Lecture Notes Series on MIT 6.S897 Machine Learning for Healthcare, Spring 2019

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MIT 6.S897 Machine Learning for Healthcare, Spring 2019 By Lecture Notes together!

Lecture 1: 1. What Makes Healthcare Unique?

Lecture 2: 2. Overview of Clinical Care

Lecture 3: 3. Deep Dive Into Clinical Data

Lecture 4: 4. Risk Stratification, Part 1

Lecture 5: 5. Risk Stratification, Part 2

Lecture 6: 6. Physiological Time-Series

Lecture 7: 7. Natural Language Processing (NLP), Part 1

Lecture 8: 8. Natural Language Processing (NLP), Part 2

Lecture 9: 9. Translating Technology Into the Clinic

Lecture 10: 10. Application of Machine Learning to Cardiac Imaging

Lecture 11: 11. Differential Diagnosis

Lecture 12: 12. Machine Learning for Pathology

Lecture 13: 13. Machine Learning for Mammography

Lecture 14: 14. Causal Inference, Part 1

Lecture 15: 15. Causal Inference, Part 2

Lecture 16: 16. Reinforcement Learning, Part 1

Lecture 17: 17. Reinforcement Learning, Part 2

Lecture 18: 18. Disease Progression Modeling and Subtyping, Part 1

Lecture 19: 19. Disease Progression Modeling and Subtyping, Part 2

Lecture 20: 20. Precision Medicine

Lecture 21: 21. Automating Clinical Work Flows

Lecture 22: 22. Regulation of Machine Learning / Artificial Intelligence in the US

Lecture 23: 23. Fairness

Lecture 24: 24. Robustness to Dataset Shift

Lecture 25: 25. Interpretability