Machine Learning for Healthcare by Prof. Peter Szolovits and Prof. David Sontag via MIT
Machine Learning for Healthcare free videos and free material uploaded by Massachusetts Institute of Technology Staff .
Introduction:
What Makes Healthcare Unique?
Overview
of Clinical Care
Deep Dive
into Clinical Data
Risk Stratification, Part 1
Discussant: Leonard D'Avolio
Risk
Stratification, Part 2
Physiological
Time-Series
Natural Language Processing (NLP), Part 1
Discussant: Katherine Liao
Natural
Language Processing (NLP), Part 2
Translating Technology into the Clinic
Discussant: Adam Wright
Machine Learning for Cardiology
Guest
Lecture: Rahul Deo
Machine
Learning for Differential Diagnosis
Machine Learning for Pathology
Guest
Lecture: Andy Beck
Machine Learning for Mammography
Guest
Lecture: Connie Lehman, Adam Yala
Causal
Inference, Part 1
Causal Inference,
Part 2
Reinforcement Learning, Part 1
Guest
Lecture: Fredrik Johansson
Reinforcement Learning, Part 2
Guest Lecture: Barbra Dickerman
Evaluating
Dynamic Treatment Strategies
Disease
Progression & Subtyping, Part 1
Disease
Progression & Subtyping, Part 2
Precision
Medicine
Automating
Clinical Workflows
Regulation of ML/AI in the US
Guest Lecture: Andy Coravos
Human Subjects Research
Guest
Lecture: Mark Shervey
Fairness
Robustness
to Dataset Shift
This course introduces students to machine learning in healthcare, including the nature of clinical data and the use of machine learning for risk stratification, disease progression modeling, precision medicine, diagnosis, subtype discovery, and improving clinical workflows.
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