NCT06899490

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

Machine Learning Analysis of Lingual Colorimetry and MADRS Score in Acupuncture Patients: a Prospective Observational Study

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 350 (estimated)
• Sponsor: Dr Benoit Bataille · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

This observational study aims to assess the potential relationship between tongue colorimetry (using standardized photographic techniques) and anxiety-depression scores measured by the Montgomery-Åsberg Depression Rating Scale (MADRS) in acupuncture patients. Data will be analyzed using machine learning methods to determine whether tongue color features correlate with MADRS scores, possibly contributing to a novel, non-invasive diagnostic tool for anxiety and depression assessment in clinical practice. Participation involves only tongue photography and completion of questionnaires, without any invasive procedures or treatment modifications.

Detailed description

This prospective observational study investigates the correlation between lingual colorimetry, captured using readily available and standardized modern photographic tools (iPhone cameras), and anxiety-depression scores evaluated by the Montgomery-Åsberg Depression Rating Scale (MADRS) among patients attending routine acupuncture consultations. Participants will undergo a simple and non-invasive photographic recording of their tongue using an iPhone, ensuring consistent lighting and standardized positioning to minimize variability. Simultaneously, participants will complete the MADRS questionnaire, a widely validated instrument for assessing anxiety and depression severity. No invasive procedures or therapeutic interventions beyond their usual acupuncture care will be performed. The acquired photographic data will be analyzed using machine learning algorithms to identify potential predictive relationships between distinct colorimetric characteristics of the tongue and the MADRS scores. The objective is to determine whether lingual imaging could serve as a reliable, non-invasive biomarker or complementary diagnostic tool for assessing psychological status in clinical practice. This approach leverages everyday technology (smartphones), promoting ease of replication and broader accessibility in clinical environments. Ultimately, findings from this study could facilitate early detection and monitoring of anxiety-depressive disorders, thus enhancing individualized patient care in complementary and integrative medicine.

Conditions

• Anxiety Disorders

Timeline

• Start date: 2024-06-27
• Primary completion: 2025-12-31
• Completion: 2026-06-01
• First posted: 2025-03-28
• Last updated: 2025-03-28

Locations

1 site across 1 country: France