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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: Machine Learning Algorithms
BeginnerCourse14 hours

Featured reviews

VL

5.0Reviewed Sep 11, 2023

Delivered all it promises. Fast paces and geared to people with lots of ML knowledge. Thank you.Muchas gracias.Valdez Ladd

FW

5.0Reviewed May 8, 2023

Excellent introduction to ML and AI in the context of healthcare. Loaded with information without being overwhelming

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.

LS

5.0Reviewed Sep 27, 2020

Interesting and well crafted, it is mostly at an introductory level, but accurate and with many details regarding how to apply ML to healthcare. Worth to follow.

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!

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.

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,

SM

4.0Reviewed Sep 22, 2021

the quality of videos was great. week 4 till week 7 have some hard to learn problems, it is better to make it more clear and easier to understand.

ET

5.0Reviewed Jul 7, 2024

Great speakers, fantastic idea to have two. Also happy that they updated the course as new tech was developed. However links to articles require subscription, which limits use.

DN

4.0Reviewed Jan 3, 2021

Good course but the language needs to be simpler. Sometimes simple facts are complicated with the use of high pedigree words that don't really add much to conveying the overall message.

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.

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.

All reviews

Showing: 20 of 145

Jun Wei Tan
5.0
Reviewed Sep 27, 2020
Luigi Saetta
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