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AI Better Than Dermatologists At Detecting Skin Cancer, Study Finds (cbsnews.com)
An anonymous reader quotes a report from CBS News: For the first time, new research suggests artificial intelligence may be better than highly-trained humans at detecting skin cancer. A study conducted by an international team of researchers pitted experienced dermatologists against a machine learning system, known as a deep learning convolutional neural network, or CNN, to see which was more effective at detecting malignant melanomas. The results? 'Most dermatologists were outperformed by the CNN,' the researchers wrote in their report, published in the journal Annals of Oncology. Fifty-eight dermatologists from 17 countries around the world participated in the study. More than half of the doctors were considered expert level with more than five years' experience. Nineteen percent said they had between two to five years' experience, and 29 percent had less than two years' experience. At first look, dermatologists correctly detected an average of 87 percent of melanomas, and accurately identified an average of 73 percent of lesions that were not malignant. Conversely, the CNN correctly detected 95 percent of melanomas. The study has been published in the journal Annals of Oncology.
I think that it's the canary in the coal mine for many medical fields.
I think you are worrying about it more than is justified. My wife is a pathologist so I'm watching this issue closely but so far the net benefit seems to be positive.
Image processing neural nets are getting more powerful and more accessible for hospitals and (more importantly) large hospital networks.
I see little evidence we are danger of them getting powerful enough any time soon to start seriously denting the number of doctors needed. I think they will impact how the doctors do their job (and that's probably good) but mostly in the sense of removing a lot of needless busywork and improving quality of care.
This expands well beyond dermatologists. No reason why similar image processing techniques can't be used in radiology, reducing a health system's need to hire more radiologists. Or echocardiogram and electrocardiogram interpretation, freeing up the time of cardiologists (so less cardiologists need to be hired in the future).
I worked in a radiology clinic about 15 years ago where they were using this sort of tech to help with diagnosis. It helps the radiologist do their job better. It doesn't replace the radiologist. (or pathologist or cardiologist etc) To reduce head count you need to have it have enough of an impact to be a step function. I don't think we are in any real danger of that happening any time soon. Even if we did though it will just change some jobs. My wife is an AP/CP pathologist so instead of looking through a microscope most of the day she might end up looking at a monitor or even reading reports more like a clinical pathologist. That's not a bad thing, it's just different.