Cutting-edge research published in the journal BMJ Health & Care Informatics has unveiled an innovative approach to identifying the risk of coronary artery disease. The groundbreaking method combines facial thermal imaging and artificial intelligence technology, demonstrating an impressive level of accuracy in detecting this potentially life-threatening condition.
The research, led by a team from Tsinghua University in Beijing, China, highlighted the ability of thermal imaging to capture temperature distribution and variations on an object's surface by detecting the infrared radiation it emits. This development marks a significant advancement in the realm of medical diagnostics and risk assessment for coronary artery disease.
Paired with artificial intelligence, this method has shown great potential for evaluating diseases by detecting abnormal blood circulation and inflammation through patterns in skin temperature. It provides real-time, non-invasive measurements and is considered more efficient than traditional approaches, making it suitable for clinical use, according to the researchers.
Current methods for diagnosing coronary heart disease rely on assessing risk factors, ECG readings, angiograms, and blood tests, which are not always accurate or widely applicable. A recent study used thermal imaging of faces and an AI-assisted imaging model to diagnose coronary artery disease.
Out of 460 participants with suspected heart disease, 322 (70%) were confirmed to have the condition using this new approach. This could potentially offer a less invasive and more accurate method for diagnosing coronary artery disease compared to current practices.
The approach was about 13 per cent better at predicting coronary artery disease than the pretest risk assessment.
"The feasibility of [thermal imaging] based [coronary artery disease] prediction suggests potential future applications and research opportunities," the team said.
"As a biophysiological-based health assessment modality. [it] provides disease-relevant information beyond traditional clinical measures that could enhance [atherosclerotic cardiovascular disease] and related chronic condition assessment," they added, calling for larger studies.
(with IANS inputs)
