A team of international scientists have developed a deep learning artificial intelligence model to screen for heart defect from birth. The model can screen electrocardiogram (ECG) for signs of atrial septal defects (ASD) -- a condition that can cause heart failure and is under-reported due to a lack of symptoms before irreversible complications arise.

While ECG, takes only about a minute to detect, when humans analyse an ECG readout for known abnormalities associated with ASD, there is limited sensitivity for picking up ASD. In the study, published in the journal eClinicalMedicine, the team fed a deep learning model ECG data from 80,947 patients in the US and Japan, over 18 who underwent both ECG and echocardiogram to detect ASD.