Facial thermal imaging combined with artificial intelligence (AI) can accurately predict the presence of coronary artery disease, according to research published in BMJ Health & Care Informatics. This non-invasive and real-time approach is more effective than conventional methods and has the potential to improve diagnostic accuracy and workflow in clinical practice. The current guidelines for diagnosing coronary heart disease are not always accurate or widely applicable, and other diagnostic techniques can be time-consuming and invasive. Thermal imaging, which captures temperature patterns on the surface of objects, has emerged as a promising tool for disease assessment.

By integrating machine learning technology, the researchers developed an AI-assisted imaging model to predict coronary artery disease using thermal imaging of the face. The approach was around 13% better at predicting coronary artery disease compared to conventional risk assessments. The study also identified traditional risk factors for the disease. The researchers highlight the need for further investigations with larger sample sizes and diverse populations to validate the findings and explore potential applications and research opportunities.