Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study.

ABSTRACT:

Background

Conventional approaches for major depressive disorder (MDD) screening rely on two effective but subjective paradigms: self-rated scales and clinical interviews. Artificial intelligence (AI) can potentially contribute to psychiatry, especially through the use of objective data such as objective audiovisual signals.

Objective

This study aimed to evaluate the efficacy of different paradigms using AI analysis on audiovisual signals.

Methods

We recruited 89 participants (mean age, 37.1 years; male: 30/89, 33.7%; female: 59/89, 66.3%), including 41 patients with MDD and 48 asymptomatic participants. We developed AI models using facial movement, acoustic, and text features extracted from videos obtained via a tool, incorporating four paradigms: conventional scale

SUBMITTER: Chen D 

PROVIDER: S-EPMC12143584 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature