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

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.

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Publication Details

Journal
Frontiers in Psychiatry
Published
2026-03-13
DOI
https://doi.org/10.3389/fpsyt.2026.1792429
Primary Topic
Digital Mental Health Interventions
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Bita Akram, Seyyedali Hosseinalipour, Rajeev Sahay, Maryam Ebrahimi
Frontiers in Psychiatry
Digital Mental Health Interventions
article

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

Bita Akram, Seyyedali Hosseinalipour, Rajeev Sahay, Maryam Ebrahimi
article en

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.

Frontiers in PsychiatryVol. 17
Sharif University of Technology (IR), North Carolina State University (US), University of San Diego (US), UC San Diego Health System (US), North Central State College (US), Artificial Intelligence in Medicine (Canada) (CA), University at Buffalo, State University of New York (US)
National Science Foundation, Division of Electrical, Communications and Cyber Systems
Quality Education
Openalex Percentile: Top 27%
Digital Mental Health Interventions
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