An artificial intelligence (AI) algorithm, derived from the features of individual heartbeats recorded on an ECG (electrocardiogram), can accurately predict diabetes and pre-diabetes, suggests preliminary research.
If validated in larger studies, the approach could be used to screen for the disease in low-resource settings, say the researchers.
Families with at least one known case of type 2 diabetes and living in Nagpur, India were enrolled in the study.
The prevalence of both type 2 diabetes and pre-diabetes was high – around 30% and 14%, respectively. The prevalence of insulin resistance was also high – 35%.
Based on the shape and size of individual heartbeats, the algorithm quickly detected diabetes and pre-diabetes with an overall accuracy of 97% and a precision of 97%, irrespective of influential factors, such as age, gender, and coexisting metabolic disorders.
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