AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine.



AI For Medical Treatment
This course is part of AI for Medicine Specialization



Instructors: Pranav Rajpurkar
Access provided by Coursera Learning Team
25,937 already enrolled
(523 reviews)
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What you'll learn
Estimate treatment effects using data from randomized control trials
Explore methods to interpret diagnostic and prognostic models
Apply natural language processing to extract information from unstructured medical data
Skills you'll gain
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There are 3 modules in this course
In this week, you will learn: How to analyze data from a randomized control trial, interpreting multivariate models, evaluating treatment effect models, and interpreting ML models for treatment effect estimation.
What's included
12 videos4 readings1 assignment1 programming assignment3 ungraded labs
In this week, you will learn how to extract disease labels from clinical reports, and also question answering with BERT.
What's included
10 videos1 assignment1 programming assignment3 ungraded labs
In this week, you will learn how to interpret deep learning models, and also feature importance in machine learning.
What's included
9 videos4 readings1 assignment1 programming assignment3 ungraded labs
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Reviewed on Jun 7, 2020
Great Course overall, I felt that week-1 is a bit theoretical rest is fine. Glad to learn about the interpretation of models.
Reviewed on Jun 13, 2020
A very nice course and specialization as well. Offers so much to learn even for those who are pure machine learners.Instructors were fantastic.Assignments were challenging but excellent.
Reviewed on Nov 15, 2020
State of the art applications of machine learning and causal inference in the field. Great update to my skills and data scientist.
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