This technology could be aah-mazing!
Researchers in Iraq and Australia say they have developed a computer algorithm that can analyze the color of a person’s tongue to detect their medical condition in real-time — with 98% accuracy.
“Typically, people with diabetes have a yellow tongue; cancer patients a purple tongue with a thick greasy coating; and acute stroke patients present with an unusually shaped red tongue,” explained senior study author Ali Al-Naji, who teaches at Middle Technical University in Baghdad and the University of South Australia.
“A white tongue can indicate anemia; people with severe cases of COVID-19 are likely to have a deep red tongue,” Al-Naji continued. “An indigo or violet-colored tongue indicates vascular and gastrointestinal issues or asthma.”
Al-Naji says his proposed imaging system mimics the traditional Chinese medicine practice of examining the tongue for signs of disease.
5,260 images were used to train the artificial intelligence model to identify tongue color and the corresponding condition. Researchers tested it with 60 tongue images from two teaching hospitals in the Middle East.
Patients sat about 8 inches from a laptop equipped with a webcam, which took a pic of their tongue. The program was able to determine the disease in almost all cases.
Findings were published in the journal Technologies.
Study co-author Javaan Chahl, a professor at the University of South Australia, says the technology will eventually be used for a smartphone app that can diagnose diabetes, stroke, anemia, asthma, liver and gallbladder problems, COVID-19 and other conditions.
“These results confirm that computerized tongue analysis is a secure, efficient, user-friendly and affordable method for disease screening that backs up modern methods with a centuries-old practice,” Chahl said.
There are still some hurdles to overcome, including patient reluctance to provide data and reflections captured by the camera misleading the algorithm.
Also, a 2023 review of five years’ worth of AI tongue image analyses raised concern about researchers having to build their own data sets because there isn’t a definitive data set.
However, the technology was found to have “enormous value” for the diagnosis and treatment of diseases.
