"This AI tools have a real chance to make a difference," said Eric Topol, a cardiologist and geneticist at Scripps Research in San Diego, and author of "The Toolkit". a forthcoming book on the use of machine learning in health care, which did not participate in the research. . "But it will take a while."

Using neural network technology, Dr. Zhang developed systems that could analyze eye scans to detect haemorrhages, lesions and other signs of diabetic blindness. Ideally, such systems would be a first line of defense to screen patients and target those who require more attention.

Dr. Zhang and his colleagues have now created a system that can diagnose an even wider range of conditions, recognizing patterns in the text, not just in medical images. The new system analyzed the electronic medical records of nearly 600,000 patients at the Guangzhou Children's and Women's Medical Center, a hospital in southern China.

First, a group of qualified doctors annotated the Guangzhou records by adding tags identifying the information. related to certain medical conditions. The system then analyzed the tagged data. When the operation was performed and new data was presented (the symptoms of a patient determined during a physical examination), he was able to establish connections himself. .

When tested on untagged data, the system could compete with system performance. experienced doctors. The diagnosis of asthma was accurate to more than 90%; the accuracy of the physicians participating in the study ranged from 80 to 94%. To diagnose gastrointestinal diseases, the system was accurate at 87%, compared to 82 to 90% for physicians.

The experts stated that in-depth clinical trials are now needed, especially given the difficulty in interpreting decisions made by neural networks.

"Medicine is a slowly evolving field," said Ben Shickel, a researcher at the University of Florida, specializing in the use of in-depth learning for care health. "Nobody will just deploy one of these techniques without rigorous tests that show exactly what's going on."