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Avis et commentaires pour d'étudiants pour Fundamentals of Machine Learning for Healthcare par Université de Stanford

191 évaluations
54 avis

À propos du cours

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....

Meilleurs avis

8 sept. 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.

1 avr. 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,

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26 - 50 sur 56 Avis pour Fundamentals of Machine Learning for Healthcare

par Jau-Jie Y

12 juil. 2021

I would like to thanks to both instructor, Professor Matthew Lungren and Professor Serena Yeung. They explain fairly clear of some concept, and it help me much. I mistake some ideal of cross entropy, loss function, etc.

And how to solve the underfitting/overfitting section is very useful.

Special thanks to both teachers.

par Gonzalo R

19 janv. 2022

Very interesting introductory course about ML in Healthcare, with a good introduction in the statistical key concepts to understand the way hoy ML works and things to care about to reduce errors and biases.

par Sandro M

20 août 2021

Conteúdo ótimo! Traz uma boa base de conceitos e aplicações para qualquer profissional que queira entender as aplicações de machine learning na área de saúde.

par María F R E

16 janv. 2022

A​lthough it is said is just basic stuff, it changed my way of analyzing the papers of AI in medicine

par Chetan D

4 mars 2021

Excellent introductory course to understand Machine Learning in the context of Healthcare delivery

par Mike W

4 déc. 2020

great overview to explain ML to all members of a team developing healthcare applications of AI

par Kushal A S

17 oct. 2020

Nicely Framed and Executed in a simple language so anyone can catch up earliest.

par Kent H

12 janv. 2021

Great course. Thank you so much for the time and effort putting it together.

par NADY E B

6 déc. 2020

A bit too technical yet very interesting. Excellent course. Thanks!

par BALU P

19 juil. 2021

great instructors and all concepts explained in very easy terms

par blue a

20 déc. 2020

Tremendous learning and outstanding presentation of concepts.

par Ann V G

3 oct. 2020

An excellent introduction. Concise. Helpful citations.

par Vera S

20 oct. 2021

The instructors are both so knowledgeable and adorable!

par Anton L

21 oct. 2020

Outstanding team performance by the two lecturers

par Lori S

14 mars 2021

"a labor of love' indeed; wonderful ! thank you!

par Vincent C G

10 nov. 2021

Amazing Good instructors, i really enjoyed them

par Kabakov B

6 oct. 2020

101 to ML. Like Ng's book ML Yearning.

par Jiameng L

26 sept. 2021

Super helpful and engaging course

par Vasilis V

25 janv. 2021

very elaborate and well organized

par Sauranshu P

22 juil. 2021


par Ernesto R

3 mai 2021


par Claudia K

7 oct. 2020

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.

par Sana M

22 sept. 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.

par Bui M H

4 oct. 2021

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

par Edwin K G

26 févr. 2021

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