Generative AI for precision neuroimaging biomarker development in psychiatry

The explosion of generative AI offers promise for neuroimaging biomarker development in psychiatry, but effective adoption of AI methods requires clarity with respect to specific applications and challenges. These center on dataset sizes required to robustly train AI models along with feature select...

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Bibliographic Details
Published in:Psychiatry research 2024-09, Vol.339, p.115955, Article 115955
Main Authors: Wright, Susan N., Anticevic, Alan
Format: Article
Language:English
Subjects:
Biomarkers
Drug discovery
Generative AI
Neuroimaging
Precision psychiatry
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Summary:The explosion of generative AI offers promise for neuroimaging biomarker development in psychiatry, but effective adoption of AI methods requires clarity with respect to specific applications and challenges. These center on dataset sizes required to robustly train AI models along with feature selection that capture neural signals relevant to symptom and treatment targets. Here we discuss areas where generative AI could improve quantification of robust and reproducible brain-to-symptom associations to inform precision psychiatry applications, especially in the context of drug discovery. Finally, this communication discusses some challenges that need solutions for generative AI models to advance neuroimaging biomarkers in psychiatry.
ISSN:0165-1781
1872-7123
1872-7123
DOI:10.1016/j.psychres.2024.115955