Chevron Left
返回到 AI for Medical Diagnosis

学生对 提供的 AI for Medical Diagnosis 的评价和反馈

941 个评分
221 条评论


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!


151 - AI for Medical Diagnosis 的 175 个评论(共 223 个)

创建者 Rodica A

Jul 15, 2020

Some Courses are good.

创建者 Lee, B

Apr 28, 2020

Thank you very much.

创建者 Yi-Chen W

May 28, 2020

Very useful course!

创建者 Leopoldo C

May 16, 2020

Excellent material!

创建者 Y P S

Aug 12, 2020

Excellent Session

创建者 Abhishake G

Aug 05, 2020

Excellent course.


May 31, 2020

The great course.

创建者 赵志斌

May 24, 2020

Very good lesson!

创建者 DANG M K

May 10, 2020

Perfect course

创建者 Julio E F

Jun 22, 2020

Great course!

创建者 Franco T

Apr 22, 2020

Great Course!

创建者 Ricardo A F S

Aug 07, 2020

Great course

创建者 Anamitra M

Jul 19, 2020

Great course

创建者 ahmed g m

May 21, 2020

great course

创建者 鲁伟

May 13, 2020

great course

创建者 Keerthi G

Jul 18, 2020


创建者 Kamlesh C

Jun 15, 2020


创建者 Santiago G

Apr 24, 2020


创建者 Ajay K

Apr 25, 2020






创建者 Bikash K k

Jul 15, 2020


创建者 DR. M E

May 20, 2020


创建者 Ana C S B

Jun 06, 2020


创建者 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.

创建者 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.

创建者 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