Reliability of noninvasive hyperspectral tongue diagnosis for menstrual diseases using machine learning method.

The outward appearance of human tongue can reflect changes in blood circulation caused by pathological states, and it has been used as an assisted method for clinical diseases diagnosis for thousands of years in China. The purpose of this study is to observe the changes in the tongue of patients with menstrual-related diseases in hyperspectral imaging and to explore the value of hyperspectral tongue imaging combining with machine learning algorithm (HSI-ML) in the diagnosis of menstrual diseases (MD). Hyperspectral tongue images are collected from 429 patients with five different kinds of MD and 52 participants with normal menstruation.