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Federated foundation models for psychiatry: a new paradigm for diagnosis, prognosis, and treatment of mood disorders

  • Sharif University of Technology
  • UC–San Diego
  • North Carolina State University

Research output: Contribution to journalArticlepeer-review

Abstract

Multimodal Multitask Federated Foundation Models (M3T-FedFMs) represent a new frontier in artificial intelligence (AI), enabling integration of diverse data modalities and multitask learning while preserving data confidentiality through federated learning. Although still in their infancy, these models hold immense promise for advancing psychiatric research, particularly in the characterization and assessment of mood disorders. In this perspective paper, we articulate a forward-looking vision for deploying M3T-FedFMs in psychiatric practice and delineate key challenges and open research directions critical for realizing next-generation, AI-driven mental health care.

Original languageEnglish
Article number1792429
JournalFrontiers in Psychiatry
Volume17
DOIs
StatePublished - 2026

Keywords

  • federated learning
  • foundation models
  • mental health
  • multimodal multitask learning
  • psychiatry

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