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Fundamentals of Machine Learning for Healthcare(으)로 돌아가기

스탠퍼드 대학교의 Fundamentals of Machine Learning for Healthcare 학습자 리뷰 및 피드백

4.8
별점
233개의 평가
66개의 리뷰

강좌 소개

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 The Stanford University School of Medicine is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians. Visit the FAQs below for important information regarding 1) Date of original release and Termination or expiration date; 2) Accreditation and Credit Designation statements; 3) Disclosure of financial relationships for every person in control of activity content....

최상위 리뷰

AJ

2020년 9월 8일

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.

LA

2021년 4월 1일

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,

필터링 기준:

Fundamentals of Machine Learning for Healthcare의 68개 리뷰 중 51~68

교육 기관: Jiameng L

2021년 9월 26일

Super helpful and engaging course

교육 기관: Vasilis V

2021년 1월 25일

very elaborate and well organized

교육 기관: Mike S

2022년 2월 10일

Concise and to the Point!!!

교육 기관: Philip T F

2022년 7월 10일

Very Interesting Course

교육 기관: Faizy H

2022년 3월 27일

very engaging!

교육 기관: Sauranshu P

2021년 7월 22일

Good

교육 기관: Ernesto R

2021년 5월 3일

Good

교육 기관: Claudia K

2020년 10월 7일

It is really good overview for people coming from a commercial background but it is done in a pretty fast manner such that I need to listened into videos again to appreciate the concept. A lot more work and reading needed to really get myself on board. I suggest a even more basic AI course prior to this module. Otherwise, if you are from Healthcare, the first 2 modules structure overviews (also very good but more US-centric) are good revisions and segway into the later module.

교육 기관: Sana M

2021년 9월 22일

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.

교육 기관: Bui M H

2021년 10월 4일

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

교육 기관: Edwin K G

2021년 2월 26일

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

교육 기관: Mahdi Z

2021년 8월 29일

very good and fun, maybe would've been better with more Instances, not just talking (last2/3 weeks)

교육 기관: Alena K

2021년 12월 12일

I​ enjoyed the course but for a beginner some lectures were hard to follow

교육 기관: liz a

2021년 1월 2일

it was a very interesting course and look forward to taking more.

교육 기관: Dasa G

2020년 12월 26일

Great instructors. The mathematical part threw me off as an MD.

교육 기관: Anushka B

2022년 1월 28일

very informative

교육 기관: Deepika P

2022년 1월 10일

the course can be made more better and effective y including real-world healthcare case studies

교육 기관: Zakir S

2020년 11월 13일

I was hoping to learn with hands on assignments but unfortunately it was mostly lectures.