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Opiniones y comentarios de aprendices correspondientes a Fundamentals of Machine Learning for Healthcare por parte de Universidad de Stanford

212 calificaciones
59 reseña

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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....

Principales reseñas


8 de sep. de 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 de abr. de 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 de 61 revisiones para Fundamentals of Machine Learning for Healthcare

por Jau-Jie Y

12 de jul. de 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.

por Jonathan W

2 de feb. de 2022

Through out the course real world examples are shared to provide context. The recommended reading provides both broader and deeper insight. As a non physician I found the ethics papers really interesting read and helped provide me with greater perspective of some of the challenges in healthcare.

por Gonzalo R

19 de ene. de 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.

por Sandro M

20 de ago. de 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.

por María F R E

16 de ene. de 2022

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

por Chetan D

4 de mar. de 2021

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

por Mike W

4 de dic. de 2020

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

por Kushal A S

17 de oct. de 2020

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

por Kent H

12 de ene. de 2021

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

por Raimundo N

28 de mar. de 2022

So grateful for this learning journey with the prestigious Stanford!

por NADY E B

6 de dic. de 2020

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

por BALU P

19 de jul. de 2021

great instructors and all concepts explained in very easy terms

por blue a

20 de dic. de 2020

Tremendous learning and outstanding presentation of concepts.

por Ann V G

3 de oct. de 2020

An excellent introduction. Concise. Helpful citations.

por Vera S

20 de oct. de 2021

The instructors are both so knowledgeable and adorable!

por Anton L

21 de oct. de 2020

Outstanding team performance by the two lecturers

por Lori S

14 de mar. de 2021

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

por Vincent C G

10 de nov. de 2021

Amazing Good instructors, i really enjoyed them

por Kabakov B

6 de oct. de 2020

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

por Jiameng L

26 de sep. de 2021

Super helpful and engaging course

por Vasilis V

25 de ene. de 2021

very elaborate and well organized

por Mike S

10 de feb. de 2022

Concise and to the Point!!!

por Faizy H

27 de mar. de 2022

very engaging!

por Sauranshu P

22 de jul. de 2021


por Ernesto R

3 de may. de 2021