A groundbreaking study has revealed that a computer algorithm can predict various diseases with 98% accuracy by analyzing the color of the human tongue.
This innovative imaging system, developed by researchers from Iraq’s Middle Technical University (MTU) and the University of South Australia (UniSA), shows promise in diagnosing a range of health conditions, including diabetes, stroke, anemia, asthma, liver and gallbladder disorders, COVID-19, and various vascular and gastrointestinal issues.
The research team trained machine learning algorithms using 5,260 tongue images to detect subtle color differences associated with different diseases.
The images were collected from patients with various health conditions at two teaching hospitals in the Middle East. In almost every case, the artificial intelligence (AI) model was able to correctly match the tongue color to the corresponding disease.
The study, published in Technologies, outlines how the system uses tongue color analysis to provide an instant diagnosis, demonstrating the potential of AI to revolutionize medical diagnostics.
According to Senior Author, Adjunct Associate Professor Ali Al-Naji from MTU and UniSA, this AI system is essentially replicating a 2,000-year-old diagnostic technique used in traditional Chinese medicine, where the tongue’s color, shape, and thickness are examined to detect health issues.
Professor Al-Naji explained that different tongue colors are indicative of various health conditions. For instance, people with diabetes often have a yellow tongue, while cancer patients might present with a purple tongue that has a thick, greasy coating.
Patients who have suffered an acute stroke typically have a red, unusually shaped tongue. A white tongue can be a sign of anemia, while a deep red tongue has been associated with severe cases of COVID-19.
Additionally, an indigo or violet tongue color can indicate vascular and gastrointestinal problems or asthma.
During the study, cameras were positioned 20 centimeters away from the patients’ tongues to capture their color. The imaging system was able to predict the patients’ health conditions in real-time, highlighting the potential of this technology for quick and non-invasive diagnostics.
Co-author Professor Javaan Chahl from UniSA suggested that this technology could eventually be integrated into smartphones, allowing people to diagnose diseases using their mobile devices.
“These results confirm that computerized tongue analysis is a secure, efficient, user-friendly, and affordable method for disease screening that supports modern diagnostic methods with an ancient practice,” Professor Chahl said.
The success of this AI system not only underscores the value of traditional diagnostic practices but also opens the door to new, accessible, and cost-effective ways of screening for diseases.
As the technology continues to evolve, it could become a vital tool in both clinical settings and for personal health monitoring, potentially improving early detection and treatment of various conditions.
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The research findings can be found in Technologies.
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