Thermal Imaging: A Promising Tool in Disease Diagnosis with the Help of Artificial Intelligence
Thermal imaging of faces is a promising tool for disease diagnosis, but it requires a combination of a thermal camera and artificial intelligence trained on data. Researchers have found that temperature differences in different parts of the face can reveal various symptoms such as diabetes and high blood pressure. In fact, a two-week fitness test was shown to reduce the “thermal age” of the face by up to five years.
A study led by Jing-Dong Han of Peking University used temperature models and AI to interpret facial thermal patterns. The researchers recorded thermal readings of over 2,800 Chinese volunteers aged 21-88 using a hand-held thermal camera. The AI created by the researchers was able to accurately predict a person’s “thermal age” based on these images alone.
The study also found that certain temperature changes in the face were associated with age and health conditions. For example, nasal temperatures decreased with age faster than other parts of the face, while temperatures around the eyes usually rose with age. The AI could also detect metabolic problems and elevated blood pressure based on facial temperature patterns.
While this approach has shown promise, further testing is needed to validate its accuracy and effectiveness in disease determination. For example, researchers are now exploring whether thermal imaging of the face could predict sleep disorders or cardiovascular diseases in different population groups.
In conclusion, thermal imaging of faces is an exciting tool for disease diagnosis that requires a combination of a thermal camera and artificial intelligence trained on data. While this approach has shown promise in predicting aging speed and health status, further research is needed to fully understand its potential applications in disease detection.
