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AI in Medicine | Medical Imaging Classification (TensorFlow Tutorial)

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Siraj Raval

Can AI be used to detect various diseases from a simple body scan? Yes! Normally, doctors train for years to do this and the error rate is still relatively high. From mammograms to cat scans, AI can diagnose a disease better than any human can if given the right training dataset. This will drastically reduce patient death, save medical practices a lot of money, and aid doctors in the patient care process. Everyone will win and its important to remember that AI won’t replace doctors, it will become the most powerful tool they’ve ever used. And once enough AI startups start impacting the field of healthcare, it will become as common a tool as the stethoscope has been.

Code for this video:
https://github.com/llSourcell/AI_in_Medicine_Clinical_Imaging_Classification

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27 thoughts on “AI in Medicine | Medical Imaging Classification (TensorFlow Tutorial)”

  5. hi, guy. I am from China.I want to know how to begin with AI learning, I want to consult you, could you give me you contact methods,so i can commute to you?

  10. Guys I need your help. I really want to play with the diabetic retinopathy (DR) dataset but it seems I can't download it on kaggle. Does anyone else have the same problem? Where can I get those datasets?

  13. I'm a radiologist working on AI/ML projects. I agree that AI/ML has a tremendous potential to HELP doctors including radiologists especially by removing the mundane repetitive work so they can focus more on quality rather than quantity. However, it also has an equal opportunity of being used for cost cutting for huge mega corps and insurance companies.

    The current trend is "AI better than Doctor/human X" which I believe is an improper metric designed to commercialize AI/ML. A better more accurate metric would be AI/ML helps doctor X save more lives. "AI/ML supervised by doctors or AI/ML supporting doctors in their practice" is the perfect set up but if we're not careful, it might turn into Machines Replacing Doctors everywhere because they're "cheaper for mass production, faster, don't complain, and are more readily replaced when obsolete." AI/ML is currently learning only with "correlation" and still cannot compete with the human brain's capacity for "cause-and-effect" which is a key differentiating factor between man and machine (but will businesses care about that?).

    I hope that more doctors become engaged in the #democratizeAI movement and your #100DaysOfMlCode.

    btw, love your videos Siraj. Keep learning a lot from them. I usually only watch and like but had to speak up about this since medicine and Radiology are near and dear to me. I really hope AI/ML is used for the betterment of health care, and not increased economic/production output.

  22. I'm a BME Undergrad and I'm gonna be attempting to build a classifier this weekend at Shellhacks in Miami. If anybody's got medical datasets on anything please message me.

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