A really useful analysis of the use of AI-based tools over the past 18 months. The disappointing conclusion is based on a catalog of errors and lack of discipline in the use of AI across a wide range of tools. Here is a great reminder….if we needed it….that the application of AI in digital health is still in its early stages. Some important lessons here.
In the end, many hundreds of predictive tools were developed. None of them made a real difference, and some were potentially harmful.
She and her colleagues have looked at 232 algorithms for diagnosing patients or predicting how sick those with the disease might get. They found that none of them were fit for clinical use. Just two have been singled out as being promising enough for future testing.
“It’s shocking,” says Wynants. “I went into it with some worries, but this exceeded my fears.”