Black-Box Algorithms: Ready For Medical Use? : Shots

Black-Box Algorithms: Ready For Medical Use? : Shots – Health News It’s hard for humans to check algorithms that computers devise on their own.

Zech and his medical school colleagues discovered that the Stanford algorithm to diagnose disease from X-rays sometimes “Cheated.” Instead of just scoring the image for medically important details, it considered other elements of the scan, including information from around the edge of the image that showed the type of machine that took the X-ray.

Black-box algorithms are the favored approach to this new combination of medicine and computers, but “It’s not clear you really need a black box for any of it,” says Cynthia Rudin, a computer scientist at Duke University.

She is pushing back against a trend in the field, which is to add an “Explanation model” algorithm that runs alongside the black-box algorithm to provide clues about what the black box is doing.

Shah developed an algorithm that could scan medical records for people who had just been admitted to the hospital, to identify those most likely to die soon.

It is equally important to avoid misuse of an algorithm, for example if a health insurer tried to use Shah’s death-forecasting algorithm to make decisions about whether to pay for medical care.

“I firmly believe that we should be thinking about algorithms differently,” Shah says.

This article was summarized automatically with AI / Article-Σ ™/ BuildR BOT™.

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