An AI system developed by Google researchers can decide when to trust AI-based decisions about medical diagnoses, and when to refer to a human doctor for a second opinion.
Medical AIs can diagnose diseases from images such as X-rays, but usually fail to judge when they might be wrongsystem developed by Google can decide when to trust AI-based decisions about medical diagnoses and when to refer to a human doctor for a second opinion. Its creators claim it can improve the efficiency of analysing medical scan data, reducing workload by 66 per cent, while maintaining accuracy – but it has yet to be tested in a real clinical environment.
The system, Complementarity-driven Deferral-to-Clinical Workflow , works by helping predictive AI know when it doesn’t know something – heading off issues with the latest AI tools that can make up facts when they don’t have reliable answers. It is designed to work alongside existing AI systems, which are often used to interpret medical imagery such as chest X-rays or mammograms. For example, if a predictive AI tool is analysing a mammogram, CoDoC will judge whether the perceived confidence of the tool is strong enough to rely on for a diagnosis or whether to involve a human if there is uncertainty.
“For systems where you have no chance to influence, post-hoc, what comes out the black box, it seems like a good idea to add on machine learning,” she says. “Whether it brings AI that’s going to be there with us all day, every day for our routine work any closer, I don’t know.”
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