The new deep-learning system beat less experienced pediatricians at detecting illnesses including meningitis and flu.
The study: The system was trained on medical records from 1.4 million visits by 567,498 patients under 18 to a medical center in Guangzhou, China. A team distilled this information into keywords linked to different diagnoses, and then fed these into the system to help it detect one of 55 diseases.
How did it do? Pretty well. The system managed to diagnose conditions ranging from common ailments like influenza and hand-foot-mouth disease to life-threatening conditions like meningitis with 90% to 97% accuracy. Its accuracy was compared with that of 20 pediatricians. It managed to outperform the junior ones, but more senior doctors had a higher success rate. The findings are described in a paper in Nature Medicine this week.
Potential uses: AI systems have shown huge promise within the field of diagnosis. But they’re still a long way from replacing, rather than merely aiding, doctors. This sort of system could be useful for triage purposes in emergency care.
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