Observational Study Using Machine Learning to Link Tongue Color and Anxiety-Depression Scores in Acupuncture Patients

What this Trial Is About

This observational study investigates the relationship between tongue color features and anxiety-depression levels in patients receiving acupuncture. Researchers aim to see if tongue photographs taken with standard smartphone cameras can predict scores on the Montgomery-sberg Depression Rating Scale MADRS, which measures anxiety and depression severity. The goal is to explore a new, non-invasive way to assess mental health using machine learning analysis. Participants will have their tongues photographed using an iPhone under standardized conditions to ensure consistent lighting and positioning. They will also complete the MADRS questionnaire during a routine acupuncture visit. No treatments or invasive procedures will be changed or added during the study. The collected data will be analyzed with machine learning methods to identify patterns between tongue color and anxiety-depression scores. During the study, participants only need to attend one visit where tongue images and questionnaire responses are collected. Researchers will measure the correlation between tongue color metrics and MADRS scores at this single timepoint. There are no additional treatments or follow-ups required. The study uses everyday technology to make this assessment easy and accessible in clinical settings, aiming to improve early detection and monitoring of anxiety and depression.

"Machine Learning Analysis of Lingual Colorimetry and MADRS Anxiety-Depression Score in Acupuncture Patients"