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Stating it as "thousands of patient images a day" is misleading. It would be the same as saying you inspected "thousands of parts each day". As the radiologist further down notes, CT scans contains many slices.

While computers don't get tired, they also have a really hard time solving stuff like annotation tasks automatically. One thing is getting a good enough general performance, another is to never make critical errors. I see a huge potential for ML approaches in health care, but primarily as an aid for the health care professionals and not as a full replacement.



Maybe not right now, but there is nothing to say that it can't eventually surpass humans in effectiveness and critical error rate. 10-15 years ago people would have said "yeah self-driving cars are good, but as an aid for the driver, never as a full replacement".


Problems may only show up on a single image, so the same fatigue still applies.




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