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AI fares better than doctors at predicting deadly complications after surgery
Johns Hopkins researchers create an artificial intelligence model to mine rich, predictive data from routine ECG tests
The federally funded work by Johns Hopkins University researchers, which turns standard and inexpensive test results into a potentially lifesaving tool, could transform decision-making and risk calculation for both patients and surgeons. Hoping to create a more accurate way to predict these health risks, the Johns Hopkins team turned to the electrocardiogram, or ECG, a standard, pre-surgical heart test widely obtained before major surgery. Image caption: Stevens’ team used artificial intelligence to extract previously undetected signals in these routine heart tests that strongly predict which patients will suffer potentially deadly complications after surgery
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