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AI for Medical Prognosis (으)로 돌아가기

deeplearning.ai의 AI for Medical Prognosis 학습자 리뷰 및 피드백

4.7
별점
671개의 평가
117개의 리뷰

강좌 소개

AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This Specialization will give you practical experience in applying machine learning to concrete problems in medicine. Machine learning is a powerful tool for prognosis, a branch of medicine that specializes in predicting the future health of patients. In this second course, you’ll walk through multiple examples of prognostic tasks. You’ll then use decision trees to model non-linear relationships, which are commonly observed in medical data, and apply them to predicting mortality rates more accurately. Finally, you’ll learn how to handle missing data, a key real-world challenge. These courses go beyond the foundations of deep learning to teach you the nuances in applying AI to medical use cases. This course focuses on tree-based machine learning, so a foundation in deep learning is not required for this course. However, a foundation in deep learning is highly recommended for course 1 and 3 of this specialization. You can gain a foundation in deep learning by taking the Deep Learning Specialization offered by deeplearning.ai and taught by Andrew Ng....

최상위 리뷰

JD
2020년 6월 4일

I am a medical image analysis enthusiast. But I always wonder why I can't I combine other patient details for extending it's application. Sure this course is awesome. I really loved it !!

BM
2020년 4월 21일

This course was great and more challenging that I have expected. More focus on statistics and survival data which is important for prognosis. Course has a good flow and valuable content.

필터링 기준:

AI for Medical Prognosis 의 118개 리뷰 중 101~118

교육 기관: Santiago G

2020년 4월 29일

Thanks!

교육 기관: Ivo F s

2021년 10월 11일

G​reat

교육 기관: Jeff D

2020년 11월 9일

Thanks

교육 기관: DR. M E

2020년 5월 25일

good

교육 기관: Alex Y

2020년 7월 16일

Unfortunately, I would like to admit that a quality of Andrew Ng's courses declined since he personally stoped working on it... For example, I enjoyed very much all those side steps in material which Andrew did in explaining and giving an intuition to the things directly not related to the subject. He is a person with very wide expertise and this seemingly not related material brings most of the enjoyment I bring home from his courses. Now it is gone... The course is still good, but now it lucks its magic ...

Andrew, please come back ! :) You still have RL unexplained and many other things )))

교육 기관: Hugues D

2020년 5월 11일

Hi,

Great course. Maybe I missed something but the explanation to calculate the C_Index does not cover all cases and so the assignment is rather complicated. The Harell's C-Index algorithm is given here: "https://statisticaloddsandends.wordpress.com/2019/10/26/what-is-harrells-c-index/" and it helped me a lot.

Thanks again for course. See you at the next one.

교육 기관: Erwin J T C

2020년 5월 22일

I liked this course. Some of the concepts appeared somewhat abstract but I'll just have to review integration and derivatives. There was also a lot of syntax to learn in python but it was great to learn more about how to use numpy and pandas. Can't wait to learn more in course 3: AI in medical treatment.

교육 기관: Jintao R

2021년 1월 17일

The machine learning part is very basic and limited, and there are no deep learning related parts. But I have gained a lot of basic concepts about prognosis, including risk model, survival estimates, Kaplan Meier, hazard, etc. Overall, a decent course.

교육 기관: Karl J

2020년 9월 24일

Good introduction to these materials, but it's difficult to use this level to incorporate into research. If you want to really use this material, you have to go deeper independently, which isn't much of an issue with the proper motivation.

교육 기관: A V A

2020년 6월 21일

A good overview of the key concepts, tools and techniques used in medical prognosis with interesting Jupyter notebook exercises and assignments that illustrate the applications and allow us to work hands-on with these techniques..

교육 기관: Taiki H

2020년 5월 14일

Good practice, but i want more hands-on assignment which focuses on how to build model from scratch, for example about COX model.

교육 기관: Giulia C

2020년 10월 17일

The course is well done and the content is high quality, as in the previous course of this specialization

교육 기관: Romain G

2021년 1월 23일

Interesting content, but superficial

교육 기관: Nyonyintono J P

2020년 8월 27일

Great course. However, i miss how Andrew deconstructs everything - it completely absorbs all your curiosity. When you move to the assignments, without extra work you can fully understand how the libraries work. This however has a different approach, they absolutely open your mind up and enthuse you to do much more background work. really good stuff!

교육 기관: Irina G

2020년 6월 23일

I liked very much the first course of this specialization, but the second one is a waste of time. Too much of medical heuristics that doesn't transfer to other fields, and will be forgotten in a week after completing this course.

교육 기관: Martin S

2021년 5월 23일

The part of the course is repeating simple algebra operations from grammar school. Also grading of python labs is based on using specific command instead of validity of results. The ratio of knowledge gained / price is very low.

교육 기관: Prithviraj J

2020년 12월 13일

This course has more to do with empirical prognosis models, nothing to do with AI.

교육 기관: geoffrey a

2020년 10월 21일

Good content. Bad quality control. The QC mistakes resulted in wasting hours of student time, and coursera help desk time. It almost resulted in lost income for coursera due to refund of money being my next step I would have taken.