Woman Mouth Tongue

(Credit: Oleg Magni from Pexels)

ADELAIDE, Australia — A practice rooted in Chinese herbal medicine for over two millennia — examining the human tongue for signs of illness — has found itself at the forefront of modern health care, thanks to artificial intelligence (AI).

Tongue diagnostic systems, traditionally employed by Chinese herbalists, are gaining popularity worldwide, particularly in the context of remote health monitoring. A study conducted by researchers from the Middle Technical University (MTU) in Baghdad and the University of South Australia (UniSA) now provides further evidence of the remarkable accuracy of this technology in detecting diseases.

Engineers from MTU and UniSA harnessed the power of a USB web camera and computer to capture images of patients’ tongues, focusing on 50 individuals afflicted with conditions like diabetes, renal failure, and anemia. They then compared the captured tongue colors with a comprehensive database of 9,000 tongue images.

Leveraging advanced image processing techniques, researchers achieved a diagnostic accuracy rate of 94 percent, as compared to traditional laboratory results. The system automatically generated voicemails specifying the patient’s tongue color and the detected disease, which were sent as text messages to either the patient or their designated healthcare provider.

Engineers explored the global advancements in computer-aided disease diagnosis based on tongue color.

“Thousands of years ago, Chinese medicine pioneered the practice of examining the tongue to detect illness,” says Ali Al-Naji, adjunct associate professor at MTU and UniSA, in a university release. “Conventional medicine has long endorsed this method, demonstrating that the color, shape, and thickness of the tongue can reveal signs of diabetes, liver issues, circulatory and digestive problems, as well as blood and heart diseases.”

A doctor examines a young girl.
Photo by Los Muertos Crew from Pexels

“Taking this a step further, new methods for diagnosing disease from the tongue’s appearance are now being done remotely using artificial intelligence and a camera – even a smartphone. Computerized tongue analysis is highly accurate and could help diagnose diseases remotely in a safe, effective, easy, painless, and cost-effective way. This is especially relevant in the wake of a global pandemic like COVID, where access to health centers can be compromised,” Al-Naji explains, further elaborating on the evolution of this ancient practice in the digital age.

Distinct diseases manifest specific tongue colors: diabetes patients often exhibit a yellow tongue, while cancer patients may have a purple tongue with a thick, greasy coating. Acute stroke patients, on the other hand, may present with a red and crooked tongue.

A separate study in Ukraine from 2022 examined tongue images of 135 COVID patients using a smartphone. The results revealed that 64 percent of mild infection cases featured a pale pink tongue, 62 percent of moderate cases showed a red tongue, and a striking 99 percent of severe COVID infections correlated with a dark red tongue.

Past investigations utilizing tongue diagnostic systems have effectively identified conditions such as appendicitis, diabetes, and thyroid disease.

“It is possible to diagnose with 80 percent accuracy more than 10 diseases that cause a visible change in tongue color. In our study we achieved a 94 percent accuracy with three diseases, so the potential is there to fine tune this research even further,” notes Al-Naji.

The study is published in the journal AIP Conference Proceedings.

You might also be interested in:

Lea la versión en español en EstudioRevela.com: La ventana a la verdadera salud es tu lengua: la IA revive una práctica de 2,000 años para diagnosticar enfermedades.

About StudyFinds Analysis

Called "brilliant," "fantastic," and "spot on" by scientists and researchers, our acclaimed StudyFinds Analysis articles are created using an exclusive AI-based model with complete human oversight by the StudyFinds Editorial Team. For these articles, we use an unparalleled LLM process across multiple systems to analyze entire journal papers, extract data, and create accurate, accessible content. Our writing and editing team proofreads and polishes each and every article before publishing. With recent studies showing that artificial intelligence can interpret scientific research as well as (or even better) than field experts and specialists, StudyFinds was among the earliest to adopt and test this technology before approving its widespread use on our site. We stand by our practice and continuously update our processes to ensure the very highest level of accuracy. Read our AI Policy (link below) for more information.

Our Editorial Process

StudyFinds publishes digestible, agenda-free, transparent research summaries that are intended to inform the reader as well as stir civil, educated debate. We do not agree nor disagree with any of the studies we post, rather, we encourage our readers to debate the veracity of the findings themselves. All articles published on StudyFinds are vetted by our editors prior to publication and include links back to the source or corresponding journal article, if possible.

Our Editorial Team

Steve Fink

Editor-in-Chief

John Anderer

Associate Editor