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AI for Medical Diagnosis に戻る による AI for Medical Diagnosis の受講者のレビューおよびフィードバック



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. As an AI practitioner, you have the opportunity to join in this transformation of modern medicine. If you're already familiar with some of the math and coding behind AI algorithms, and are eager to develop your skills further to tackle challenges in the healthcare industry, then this specialization is for you. No prior medical expertise is required! This program will give you practical experience in applying cutting-edge machine learning techniques to concrete problems in modern medicine: - In Course 1, you will create convolutional neural network image classification and segmentation models to make diagnoses of lung and brain disorders. - In Course 2, you will build risk models and survival estimators for heart disease using statistical methods and a random forest predictor to determine patient prognosis. - In Course 3, you will build a treatment effect predictor, apply model interpretation techniques and use natural language processing to extract information from radiology reports. These courses go beyond the foundations of deep learning to give you insight into the nuances of applying AI to medical use cases. As a learner, you will be set up for success in this program if you are already comfortable with some of the math and coding behind AI algorithms. You don't need to be an AI expert, but a working knowledge of deep neural networks, particularly convolutional networks, and proficiency in Python programming at an intermediate level will be essential. If you are relatively new to machine learning or neural networks, we recommend that you first take the Deep Learning Specialization, offered by and taught by Andrew Ng. The demand for AI practitioners with the skills and knowledge to tackle the biggest issues in modern medicine is growing exponentially. Join us in this specialization and begin your journey toward building the future of healthcare....



Jul 03, 2020

It was a nice course. Though it covers basics. A follow-up advanced specilization can be made. Overall, it's sufficient for beginner for an engineer trying to learn application of AI for medical field


May 27, 2020

Throughout this course, I was able to understand the different medical and deep learning terminology used. Definitely a good course to understand the basic of image classification and segmentation!


AI for Medical Diagnosis: 176 - 200 / 253 レビュー


May 31, 2020

The great course.

by 赵志斌

May 24, 2020

Very good lesson!


May 10, 2020

Perfect course

by MD A R A

Sep 08, 2020

Excellent !!!

by Julio E F

Jun 22, 2020

Great course!

by Franco T

Apr 22, 2020

Great Course!

by Ricardo A F S

Aug 07, 2020

Great course

by Anamitra M

Jul 19, 2020

Great course

by ahmed g m

May 21, 2020

great course

by 鲁伟

May 13, 2020

great course

by Keerthi G

Jul 18, 2020


by Kamlesh C

Jun 15, 2020


by Santiago G

Apr 24, 2020


by Ajay K

Apr 25, 2020







Aug 28, 2020


by Bikash K k

Jul 15, 2020


by DR. M E

May 20, 2020


by Ana C S B

Jun 06, 2020


by Nirav S

May 25, 2020

Overall it is still a good course and worth doing but I won't expect to be able to clear a job interview in medical machine learning based on this course. It touches many nice topics such as what to do if data is unbalanced, different metrics about evaluating the models. However the part about MRI segmentation seems very rushed. I would consider this as a very basic course and the student would have to spend significant personal time exploring on his/her own to really understand the concepts presented in the class. It wasn't easy for me to get help on some programming assignments when I got stuck a. Moreover, when I didn't get a perfect score on the programming assignments, I don't know where I made the mistakes, which makes it impossible to correct them.

by Erwin J T C

May 08, 2020

As a Radiologist from the Philippines who has been desperately trying to find some kind of "grounded center" for all the AI/ML topics I've been studying online, this is a really great way to consolidate what I've learned so far especially for AI applied to Radiology. I've been training models for computer vision (based on free tutorials on-line) but this has definitely given me better insight as to how those models actually work and how they come together from simple numpy arrays, to tensors, layers, and finally into compiled models.... giving me a better appreciation for how activation functions and convolutions actually fit into the development of convolutional neural networks. More power to the team.

by Hossein A

Sep 14, 2020

Overall, it is a good decision to take the course. Although it focuses on practical aspects of the AI in medicine, it falls short explaining the basic CNN architecture for image segmentation or classification. That said if you wish to fully take advantage of the course, spend some time understanding some of the key functions available in the scripts which can be accessed through the notebooks. There, you could benefit from the course and learn interesting implementation stuff if you feel like the assignments are too practical.

by Vinayak

Aug 18, 2020

This is an amazing course for people who know AI and want to know about it's applications in the healthcare industry. I had fun learning from the instructor Pranav who is concise and delivers lessons comprehensively. Overall an amazing course. Could have asked for more assignments and hands-on stuff, hence I'm being conservative on granting 4-stars only...

by A V A

May 25, 2020

Very good course on applying AI for image-based medical diagnosis. Some things that could be improved are : 1. adding content relevant to using AI in non-image based diagnosis 2. could be made more comprehensive with more applications, exercises and theoretical content by extending course duration to a longer time

by Amit P

May 03, 2020

The video segments could be made longer to incorporate more information on how the modeling is done. A lot of new information was thrust into the weekly exercises. It would be better if the weekly exercises were a test of what we had learnt. A great course on the whole, anyway. The instructor was very clear.

by Vishnusai Y

May 12, 2020

Introduces the fundamentals of using AI for medical diagnoses. Concepts are clearly explained and the assignments are well framed. More lectures regarding subtle concepts like MRI Image registration and calculation of confidence interval would have made the course more interesting and comprehensive