That’s more than 10 million people, and for half of them, the misdiagnosis could be harmful, a 2014 study in the British Medical Journal concluded. Doctors try to be systematic when identifying illness and disease, but they’re only human. Bias creeps in. Alternatives are overlooked.
With a paper published Monday in Nature Medicine, a group of researchers from universities in the U.S. and China tested a potential remedy: artificial intelligence.
The researchers built a system that automatically diagnoses common childhood conditions — from influenza to meningitis — after reading a patient’s symptoms, medical history, lab results and other clinical data. The system was highly accurate, and one day could assist doctors in diagnosing patients with complex or rare conditions, the researchers said.
“In some situations, physicians cannot consider all the possibilities,” said Kang Zhang, a professor of ophthalmology, genetics and nanoengineering at the University of California, San Diego, and one of the authors of the paper. “This system can spot-check and make sure the physician didn’t miss anything.”
The system relies on a neural network, a breed of artificial intelligence that can learn tasks by analyzing vast amounts of data. In this case, it analyzed electronic health records from more than 1.3 million patient visits to a pediatric hospital in China, learning to associate common medical conditions with specific patient information gathered by doctors, nurses and other technicians.
Able to recognize patterns in data that humans could never identify on their own, neural networks can be enormously powerful in the right situation. But even experts have difficulty understanding why such networks make particular decisions. As a result, extensive testing is needed to reassure both doctors and patients that these systems are reliable.
The new system analyzed the electronic medical records of nearly 600,000 patients at the Guangzhou Women and Children’s Medical Center, a hospital in southern China.
It was more than 90 percent accurate at diagnosing asthma; the accuracy of physicians in the study ranged from 80 to 94 percent. In diagnosing gastrointestinal disease, the system was 87 percent accurate, compared to the physicians’ accuracy of 82 to 90 percent.
This article originally appeared in The New York Times.