Human and AI collaboration is far more accurate for medical diagnosis

Source: QMED, Jun 2016

A group of researchers from Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School in Boston have teamed up to develop new diagnostic methods based on artificial intelligence (AI).

The evaluation showed that their automated diagnostic method was able to produce accurate diagnostic results in 92% of the images examined, nearly matching the 96% success rate of a human pathologist. However, when the automated diagnostic method was combined with the efforts of a human pathologist, the results were rather astounding.

“When we combined our computational method with a human pathologist’s diagnoses, we increased the pathologist’s AUC(area under the receiver operating curve, or simply their success rate) to 99.5%,” Irshad said. “This represents an approximate 85 percent reduction in human error rate. These results demonstrate the power of using computational methods to produce significant improvements in the accuracy of pathological diagnoses.”


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