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Stanford University

Fundamentals of Machine Learning for Healthcare

Machine learning and artificial intelligence hold the potential to transform healthcare and open up a world of incredible promise. But we will never realize the potential of these technologies unless all stakeholders have basic competencies in both healthcare and machine learning concepts and principles. This course will introduce the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. We will explore machine learning approaches, medical use cases, metrics unique to healthcare, as well as best practices for designing, building, and evaluating machine learning applications in healthcare. The course will empower those with non-engineering backgrounds in healthcare, health policy, pharmaceutical development, as well as data science with the knowledge to critically evaluate and use these technologies. Co-author: Geoffrey Angus Contributing Editors: Mars Huang Jin Long Shannon Crawford Oge Marques In support of improving patient care, Stanford Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team. Visit the FAQs below for important information regarding 1) Date of the original release and expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content.

Status: Data Ethics
Status: Artificial Neural Networks
BeginnerCourse14 hours

Featured reviews

GM

5.0Reviewed Nov 12, 2020

Completing this course has given me a solid foundation and confidence to engage at a deeper level with AIML in health, both as a student and exponent thereof.

AJ

5.0Reviewed Sep 9, 2020

Amazing course teaching the innumerous opportunities in the healthcare sector and the application of AI in the same. Beautifully drafted course with intriguing tutorials and exercises.

MM

5.0Reviewed Oct 8, 2020

An excellent course for professionals with healthcare background, specially for those who want to test the water before diving deep into AI in Healthcare.

LA

5.0Reviewed Apr 2, 2021

This was a great course, the presenters really gave a clear view about the differences which could happen when working with health related data set. Very well done,

QB

5.0Reviewed Jul 22, 2023

This course will give you the complete information that is required by a beginner. Best if you want help to start working on ML project related to healthcare in beginning of your career.

KK

5.0Reviewed Sep 1, 2023

Mathew and Serena are excellent. I enjoyed the module. The subject matter is very dense but made palatable by these two experts. Thanks and kudos to them!

MA

5.0Reviewed Sep 21, 2025

As you said in the goodbye video, you made this with love. This course is worth more than 5 stars. Thank you, I can't be more grateful!

SI

5.0Reviewed Feb 25, 2024

I really enjoyed learning from this course . Helped me increasing my knowledge and clearing my ambiguities and misconceptions regarding the AI in healthcare.

PC

5.0Reviewed Nov 10, 2023

This is an excellent course for anyone in healthcare who is trying to learn and understand clinical machine learning.

EG

4.0Reviewed Feb 26, 2021

Would have been helpful to go through all stages of a model development top show how things tie together. Otherwise well done.

RR

5.0Reviewed Jan 2, 2021

Top quality teaching from Matthew and Serena, thank you! Engaging throughout the whole 7 weeks, best if you have some previous knowledge in ML.

BH

4.0Reviewed Oct 4, 2021

There are maybe too much scenes without slides, if you explain with slides combined, it would be more easy to understand and follow

All reviews

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