Artificial Intelligence Examining ECGs Predicts Irregular Heartbeat, Death Risk - Docwire News

Artificial intelligence can be used to accurately examine electrocardiogram (ECG) test results, according to the findings of two preliminary studies being presented at the American Heart Association Scientific Sessions 2019 in Philadelphia, PA. In the first study, researchers evaluated 1.1 million ECGs that did indicate atrial fibrillation (AF) from more than 237,000 patients. They used specialized computational hardware to train a deep neutral network to assess 30,000 data points for each respective ECG. The results showed that approximately one in three people received an AF diagnosis within a year. Moreover, the model demonstrated the capacity for long-term prognostic significance as patients predicted to develop AF after one year had a 45% higher hazard rate in developing AF over a follow-up duration of 25-years compared to other patients.