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AI-Based Tongue Imaging
Context:
Recent researchers have unveiled a novel approach to detecting coronary artery disease (CAD) using AI-based tongue imaging.
More on News:
- This innovative method combines the ancient practice of tongue diagnosis from Traditional Chinese Medicine (TCM) with cutting-edge artificial intelligence technology, offering alternative to traditional diagnostic procedures.
- The study, conducted by Beijing University of Chinese Medicine and Hunan University of Chinese Medicine, aimed to develop a safer, non-invasive, efficient, and cost-effective diagnostic method.
Key Highlights:
- According to the World Health Organisation, CAD is the leading cause of death globally, responsible for 17.9 million deaths annually, accounting for nearly one-third of all illness-related deaths.
- Coronary angiography, the gold standard for CAD diagnosis, is invasive, expensive, and not ideal for early detection or assessing risk.
- TCM emphasises external observation for diagnosing internal conditions, including tongue diagnosis, which assesses the tongue’s colour, coating, and shape as indicators of systemic health.
Study Results:
- The study involved hypertensive patients aged 18 to 85, with a final cohort comprising 244 patients with hypertension and 166 patients with both hypertension and CAD.
- The CAD diagnostic algorithm demonstrated notable performance, particularly in individuals aged 65 and older, and was equally effective across genders.
- The algorithm also showed enhanced accuracy in cases with three or more risk factors, underscoring the importance of considering multiple risk factors in CAD diagnosis.
Limitations:
- The study’s sample was limited to patients with hypertension, lacking diversity in terms of country, ethnicity, and varying diagnostic equipment.
- The model’s applicability might be restricted by the single type of equipment used for collecting tongue images.
Implications:
- Future research should involve a larger and more diverse population and consider integrating additional biomarkers.
- Expanding the study to validate and optimise the diagnostic model further is recommended.