It is an excellent course on how we should evaluate AI solutions.

I was expecting the Medical genetics professor as a teacher also.

This course was really fulfiling and I enjoyed it very much.

One of the most important courses in this specialization.

Very thorough with clear and concise information delivery

Outstanding informational content and operating platform!

Through and engaging presentation. Thank you

An excellent course. Very informative.

Best course in the program so far.

It was very beneficial.

Good course for PM's :)

THANKS VERY USEFUL

it is very good

muy buen curso

Awesome Course

Great course!

Great course!

Excellent

도움이 되었습니다

muito bom

Great

good

The course content is exceptional. Spot on and sufficiently detailed to provide complete clarity on how to evaluate AI applications in Healthcare. The additional optional module with updates is a welcome surprise. Thanks for that. One observation - and the reason for 4 stars. In the final exam, one question was wrong and despite repeated efforts and selecting all the options in turn, the LMS returned the answer as incorrect. As a result the score remained at 96% instead of 100% . The question is as below. All four of them are important settings as explained in the training video "Settings". The last option should be "None of the above" so the question can be answered correctly. 12. Which of the following is not an important setting in AI development? Academics Industry Government Philanthropy All of the above

This course contains an extraordinary amount of considerations and information critical to the process of development and deployment of AI Applications in Healthcare. The topics include Evaluation Frameworks, Deployment Methodologies, Regulatory considerations, key considerations of fairness and bias in AI Applications, and Ethical considerations in AI. In many ways, any organization that intends to or is in the process of developing AI Applications should take these topics into consideration even before development begins. The material provided includes references to helpful frameworks and guidelines, which if used in the initial stages of the life cycle of an AI Application, would probably help reduce lead time, as also enable the deployment usage of the application in actual healthcare settings.

An imporatnt topic area, but a little hard to digest as it uses a lot of terminology and frameworks which are not necessarily well defined. I think it would benefit from some simplification into principles and language that are more relatable, still cross referenced to the technical/regulator terminology.