AI predicts coronary artery disease from facial thermal imaging

AI predicts coronary artery disease from facial thermal imaging unknown

A combination of facial thermal imaging and artificial intelligence (AI) can accurately predict the presence of coronary artery disease (CAD), finds research published in the open access journal BMJ Health & Care Informatics. This non-invasive real-time approach is more effective than conventional methods and could be adopted for clinical practice to improve the accuracy of diagnosis and workflow, pending testing on larger and more ethnically diverse numbers of patients, suggest the researchers. 

Current guidelines for the diagnosis of coronary heart disease rely on probability assessment of risk factors which aren’t always very accurate or widely applicable, say the researchers. And while these can be supplemented with other diagnostics, such as ECG readings, angiograms, and blood tests, these are often time consuming and invasive, they add. 

Thermal imaging, which captures temperature distribution and variations on the object’s surface by detecting the infrared radiation emitted by that object, is non-invasive. And it has emerged as a promising tool for disease assessment as it can identify areas of abnormal blood circulation and inflammation from skin temperature patterns.