BRI-MH: Behavioral Risk Index for Mental Health — An Interpretable Multimodal LLM-Augmented Framework (Student Abstract)

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Authors: Association for Artificial Intelligence 2026, Avinash Anand, Mahi Mann, Rajiv Ratn Shah
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Abstract

Mental health monitoring faces challenges from fragmented data and opaque risk scores. We present BRI-MH, an in- terpretable multimodal framework combining behavioral sig- nals with cognitive features from large language models to produce a weekly Behavioral Risk Index. Unlike prior work with isolated or black-box scores, BRI-MH offers transpar- ent, actionable insights and links continuous monitoring to adaptive feedback and therapeutic support, bridging digital phenotyping and clinical care

Fields of Study & Subjects

Mental Health via Writing Digital Mental Health Interventions Emotion and Mood Recognition

Publication details

Journal / source
Underline Science Inc.
Publication date
7 January 2026
Language
EN