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學生對 提供的 AI for Medical Diagnosis 的評價和反饋

1,620 個評分
353 條評論


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....



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


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!


326 - AI for Medical Diagnosis 的 350 個評論(共 353 個)

創建者 Karen F


What I am finding in most Coursera courses: 1) Important topics are just glossed over in often < 3 minutes. That itself make me wonder if the courses are worth the price even.

2) Code assignments seem to take most time figuring out what the provided code does, and how I am expected to fill in a few blanks. And after completion I am far from being able to, for example, build a basic x-ray classifier from beginning to end.

創建者 Kenny F C


As other reviews have mentioned, though the course introduces important concepts for evaluating models in a medical context (confusion matrix, ROC curves), the concepts and exercises were too basic and surface level. Keep in mind the medical context is solely from the point of view of medical imaging. The autograder was also buggy and I was unable to start new topics in Discourse to ask questions about it.

創建者 Jakub V


This is interesting topic and I learnt how these things are done in medicine. However, from technical point of view, there are many issues. Bugs, typos, unexplained terms (dear learner, now please calculate background ratio) make this course messy and leaves the taste of "rushed product of corona crisis".

創建者 Volodymyr F


The course is very shallow. It explains in detail some simple concepts like Sensitivity and Specificity and then immediately touches complex topics like image recognition architectures, without much explanation. The course materials are unclear and the auto-grader is buggy.

創建者 Amina K


Instructions in the graded assignment did not have clear instructions. Sometimes, correct implementation was graded 'incorrect' by the grader. Also, videos of the ROC curve was not clear about why it is needed or what does it say about a model.

創建者 Tasneem. A


Hi Sir/Madam,

i took this course then realised it is beyond my understanding. I am a grade 12 student . please help me to cancel this ,so, i can take another course which can benefit me.

i will appreciate your help.

thanking you

創建者 Subair A


Too much task was given but less explanation. It was really hard to complete all the tasks. It would be better if easiest tasks are given or more explanation with huge explanation.

創建者 Ravi C


Expected content that would be new but found content which I was already familiar with. Disappointed a little on that. Course could have some more interesting and new content.

創建者 Harit J


Good instructor but concepts were not taught in-depth. The assignments gave only a superficial understanding of the subject and cannot prepare one for working in the industry.

創建者 Nithin


The course touches on several aspects of ML for medical. However, the content seems too little and narrow. Only a few cases and architectures are explored.

創建者 Sundeep L


Would like it if the projects were more in-depth. We should understand the end-to-end pipeline: from preprocessing to deploying in production

創建者 Laurin R


Some concepts used in the assignments are note explained in the videos e. g. the calculation of AUC.

創建者 Pedro G


The lectures are good, but I experienced many issues on homeworks.

創建者 Thiago M d O


Content is too shallow, could have gone deeper into some topics.

創建者 mohit r


The codes should have be explained ...

創建者 Andrey A


Too general for practical usage

創建者 Hanan S A


good as an introduction

創建者 Matthias K


Fairly shallow.

創建者 Apoorv G


I first took Deep Learning Specialization by Andrew and then took NLP specialization by Younes Mourri and then this course. One difference I noticed that Andrew explained all the stuff by himself in detailed 8-10 min video and here these in these two coursers, the two instructor explained concept in 1-2 min video and left the remaining concept to learned by ourselves through notebooks. Andrew put much more effort than these two guys.

創建者 Michael L


Did a good job of explaining some of the terms and processes involved in using AI for medical diagnosis, but the flow and organization of the course were really poor and the methods taught were not general enough to be able to extrapolate to use in new ways outside of the course.

創建者 Kemal U A


There is no reply or response to discussion forums from the instructors and assessment of the assignments are always zero so I can not pass to week two even my assignment's outputs are matched with the correct ones .

創建者 Duncan L


A far too brief overview of AI applications in medical diagnosis - only really covers image analysis and even then is cursory at best. Disappointing as I have found the other courses quite helpful.

創建者 krishan s


Not useful. Probability distributions are not intuitive mostly.

創建者 Sagimbayev Z


This course relays on "add one line" code too often.

創建者 Aliakbar D


I have done several of AI courses including the TensorFlow. While the TensorFlow course, gives you a neat and excellent hands on on how to build a network from scratch or implement easily a CNN such as Inception V3, this course make you confused as what sort of aim it follows. Overall confusing and not useful. Though you find some good stuff in the videos but the design and strategy of the course is meaningless.