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AI in Healthcare Capstone に戻る

スタンフォード大学(Stanford University) による AI in Healthcare Capstone の受講者のレビューおよびフィードバック



This capstone project takes you on a guided tour exploring all the concepts we have covered in the different classes up till now. We have organized this experience around the journey of a patient who develops some respiratory symptoms and given the concerns around COVID19 seeks care with a primary care provider. We will follow the patient's journey from the lens of the data that are created at each encounter, which will bring us to a unique de-identified dataset created specially for this specialization. The data set spans EHR as well as image data and using this dataset, we will build models that enable risk-stratification decisions for our patient. We will review how the different choices you make -- such as those around feature construction, the data types to use, how the model evaluation is set up and how you handle the patient timeline -- affect the care that would be recommended by the model. During this exploration, we will also discuss the regulatory as well as ethical issues that come up as we attempt to use AI to help us make better care decisions for our patient. This course will be a hands-on experience in the day of a medical data miner. 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....




Getting AI specialization Stanford University is very amazing and effective to start your AI careers. Thank you for all Stanford university lecturers, Thank you Coursera for everything !



Amazing experience, such in depth learning to understand how to approach data problems in healthcare settings and where they can actually be of benefit.


AI in Healthcare Capstone: 1 - 25 / 28 レビュー

by Siang-Hiong G


A good and thorough introduction to this exciting field which is full of unrealised potential for healthcare and medicine. For busy clinicians like me, I found the online, learn-at-your-own pace model very helpful and convenient, and well worth the affordable price. Most importantly, you DO NOT need to learn about coding or python. But I would advise you follow up on the recommended readings prescribed at the end of each week's talk. Of course, there is a bias towards American healthcare in Module 1, but this makes for interesting reading and an appreciation of the weaknesses and strengths of US health system. I only hope that regular updates on Machine Learning could be provided every 2 years or so to past participants, similarly online, as this field is ever-evolving and changing. I would not mind paying for it.

by Jun W T


If you are still not too familiar with the concepts learnt, this is a good chance to recap what was learnt that is mostly focused on Courses 3 and 4. Doing this course will help reinforce your learning.

by Amer Z


Getting AI specialization Stanford University is very amazing and effective to start your AI careers. Thank you for all Stanford university lecturers, Thank you Coursera for everything !

by Mariam C


Amazing experience, such in depth learning to understand how to approach data problems in healthcare settings and where they can actually be of benefit.

by Elizabeth M


Thank you very much now I can also code having acknowledge of everything that is important. Greetings from Peru :)

by Hmei D


Really enjoy the Capstone projects with wonderful peer-reviewing. Would recommend.

by Sayali K


An excellent course to venture into the field of 'AI in medicine'.

by Freddy F


Great real world exercises in order to apply knowledges of the other courses. Some questions required clinical background.

by Philip L


Interesting case study of the current COVID data in building AI models around them. I took the first version of the class and it has a few rough edges (grading mistakes, odd questions, missing instructions, data formatting). Even with the rough spots, the class was a thought provoking experience that required the background of the courses provided, but it also required some outside AI education and experience to come up with answers. Although I have some differences in the approach chosen by the instructors on some topics such as bias, the material is invaluable.

by Olabode A


I learned a lot in this course. The AI in Healthcare specialization covers diverse topics with a very deep introduction to Machine Learning, Deep learning, and better still AI. I really want to say thank you to all the Stanford university lecturers, and thank you Coursera for everything and wonderful for a well-done job.

by Elizabeth G


Excellent instructors! The course provided a solid foundation with broad coverage of the topic of AI in Healthcare. It was appropriate for both medical clinicians and AI developers to enable them to come together with understanding to better develop and implement valuable AI tools for future improvement of healthcare.

by akshay s


Very well structured course. Easy to understand for those without a backgraoud of bioinformatics. And of course great mentors

by Kiran S


I really enjoyed this course as it was applied learning of all I learned during the previous courses of the specialization.

by Arvind B


The quality of peer review exercises was good and the content of the reading material was well understood

by Gangadhar S


The course covers diverse topics and need very deep knowledge of Machine Learning and AI

by Kushal A S


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

by vincent y


Stanford lives up to their reputation of doing good course work.

by Kabakov B


There are 9 peer review tasks, but they are not obligate ;)

by blue a


Great program and excellent learning platform!

by Kenneth N


Very good course. worth our time

by Philip S


Excellent introduction!

by Iris C


Excellent course

by Atul P


Great team !!

by Lars W


Some technical issues with the quizzes and assignments (ie one assignment had no question, just an answer). Some fellow students cheated by copy-pasting in the correct answer after evaluating peers. Still, I liked that you had difficult in-depth questions even though we haven't done any ML projects or hands on coding.

by John J


A great summary pulling together the material taught in the previous 4 courses. Easy and straightforward to go through. There are a few items in the course that need to be cleaned up, like duplicate quiz questions with conflicting "correct" answers, and opening up the discussion forums.