A groundbreaking method for determining diseases using a thermal camera and AI models trained on data has been developed by researchers. By analyzing facial temperatures, they can predict a person’s age and state of health. The technology known as Thermo face uses temperature models and AI to interpret thermal patterns, which can indicate different symptoms such as diabetes and high blood pressure.
Peking University researchers conducted a study that involved recording thermal readings of more than 2,800 Chinese volunteers to train artificial intelligence. The AI software developed could accurately predict a person’s age and “thermal age” based on facial thermal images alone. The research also found correlations between facial temperatures and metabolic issues, blood pressure, and the activity of cells associated with inflammation.
Moreover, a fitness test involving rope jumping showed a significant reduction in participants’ “thermal age” after just two weeks of training. This demonstrates the potential impact of lifestyle changes on health indicators. Further testing is required to validate the accuracy and reliability of using thermal cameras for disease determination on diverse population groups.
In conclusion, this innovative method has the potential to revolutionize disease detection and diagnosis in the future. With further research and development, thermal imaging could become an essential tool for healthcare professionals to diagnose diseases early on, leading to better outcomes for patients.