The testing of AI in medicine is a mess. Here’s how it should be done

Mariana Lenharo in Nature:

When Devin Singh was a paediatric resident, he attended to a young child who had gone into cardiac arrest in the emergency department after a prolonged wait to see a doctor. “I remember doing CPR on this patient and feeling that kiddo slip away,” he says. Devastated by the child’s death, Singh remembers wondering whether a shorter waiting time could have prevented it.

The incident convinced him to combine his paediatric expertise with his other speciality — computer science — to see whether artificial intelligence (AI) might help to cut waiting times. Using emergency-department triage data from the Hospital for Sick Children (SickKids) in Toronto, Canada, where Singh currently works, he and his colleagues built a collection of AI models that provide potential diagnoses and indicate which tests will probably be required. “If we can predict, for example, that a patient has a high likelihood of appendicitis and needs an abdominal ultrasound, we can automate ordering that test almost instantly after a patient arrives, rather than having them wait 6–10 hours to see a doctor,” he says.

More here.

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