Carding 4 Carders
Professional
The color of the tongue can tell you a lot about a person's health.
The ancient method of Chinese herbalists, used for two thousand years, is to study the color of a person's tongue to detect signs of illness, now used by scientists in the field of machine learning and artificial intelligence.
Language-based diagnostic systems are becoming increasingly popular due to the growth of remote health monitoring. A study conducted by Iraqi and Australian scientists confirms the increased accuracy of such technologies in detecting diseases. Engineers from the Middle Technical University (MTU) in Baghdad and the University of South Australia (UniSA) used a USB webcam to capture images of the languages of 50 patients with diabetes, kidney failure and anemia, comparing colors to a database of 9,000 language images.
Using image processing methods, scientists correctly diagnosed diseases in 94% of cases, which was confirmed by laboratory results. Patients or their medical representatives were also sent a voice message indicating the color of the tongue and the diagnosis.
Professor Ali Al-Naji of MTU and UniSA and his colleagues reviewed the world's advances in computer-based diagnosis of diseases based on language color. "Thousands of years ago, Chinese medicine introduced the practice of language learning to detect diseases," says Professor Al-Naji. He also emphasizes that modern methods allow you to conduct diagnostics at a distance using AI and a camera, even a smartphone.
Diabetic patients usually have a yellow tongue, cancer patients have a purple tongue with a greasy coating, and acute stroke patients have a red, often curved tongue. A 2022 study in Ukraine found that 64% of patients with mild COVID had a pale pink tongue, 62% with moderate COVID had a red tongue, and 99% with severe COVID had a dark red tongue.
"It is possible to diagnose with 80% accuracy more than 10 diseases that cause visible discoloration of the tongue. In our study, we achieved 94% accuracy in three diseases, so there is potential for further refinement of the study," concludes Professor Al-Naji.
The ancient method of Chinese herbalists, used for two thousand years, is to study the color of a person's tongue to detect signs of illness, now used by scientists in the field of machine learning and artificial intelligence.
Language-based diagnostic systems are becoming increasingly popular due to the growth of remote health monitoring. A study conducted by Iraqi and Australian scientists confirms the increased accuracy of such technologies in detecting diseases. Engineers from the Middle Technical University (MTU) in Baghdad and the University of South Australia (UniSA) used a USB webcam to capture images of the languages of 50 patients with diabetes, kidney failure and anemia, comparing colors to a database of 9,000 language images.
Using image processing methods, scientists correctly diagnosed diseases in 94% of cases, which was confirmed by laboratory results. Patients or their medical representatives were also sent a voice message indicating the color of the tongue and the diagnosis.
Professor Ali Al-Naji of MTU and UniSA and his colleagues reviewed the world's advances in computer-based diagnosis of diseases based on language color. "Thousands of years ago, Chinese medicine introduced the practice of language learning to detect diseases," says Professor Al-Naji. He also emphasizes that modern methods allow you to conduct diagnostics at a distance using AI and a camera, even a smartphone.
Diabetic patients usually have a yellow tongue, cancer patients have a purple tongue with a greasy coating, and acute stroke patients have a red, often curved tongue. A 2022 study in Ukraine found that 64% of patients with mild COVID had a pale pink tongue, 62% with moderate COVID had a red tongue, and 99% with severe COVID had a dark red tongue.
"It is possible to diagnose with 80% accuracy more than 10 diseases that cause visible discoloration of the tongue. In our study, we achieved 94% accuracy in three diseases, so there is potential for further refinement of the study," concludes Professor Al-Naji.
