A team of researchers from organizations such as the Institute of Science Tokyo said Tuesday it has developed an artificial intelligence model that can detect a high risk of diabetes using only electrocardiogram (EKG) data.

This method, which does not require blood tests, can lead to possible early detection of the disease and help those at high risk review their lifestyles, according to the team.

Together with other team members, Tetsuya Yamada, a professor at the university, divided about 16,000 people who underwent medical checkups in Tokyo in 2022 into a group of diabetics and prediabetics, with higher-than-standard blood sugar levels, and a group of subjects with normal readings.

The team put its EKG data into an AI model to analyze minuscule changes in cardiac muscle movement that appear in the prediabetic stage. The result was that the model was able to identify people who are at high risk and who are not diabetics at about 85% and 70% accuracy, respectively.

A survey using watch-type wearable devices showed almost the same results.

Diabetes has few subjective symptoms in its early stages. It is currently difficult to detect the disease or assess the risk of developing it without a blood test. Meanwhile, completely curing patients is very hard after the onset of the disease, making detection at the prediabetic stage crucial.

Yamada noted that the study using wearable devices will be continued. "If we can link ECG data with wearable devices and integrate them into wellness apps, this can be utilized as an index to review lifestyle habits," he said, referring to electrocardiogram data.