Peer-Reviewed Publication
Patterns (N Y)2022;3(11):100602.November 11, 2022Journal Article
Modern views of machine learning for precision psychiatry.
Zhe Sage Chen1,2,3,4, Prathamesh Param Kulkarni5, Isaac R Galatzer-Levy1,6, Benedetta Bigio1, Carla Nasca1,3, Yu Zhang7,8
1Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA.
2Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA.
3The Neuroscience Institute, New York University Grossman School of Medicine, New York, NY 10016, USA.
4Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY 11201, USA.
5Headspace Health, San Francisco, CA 94102, USA.
6Meta Reality Lab, New York, NY, USA.
7Department of Bioengineering, Lehigh University, Bethlehem, PA 18015, USA.
8Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA 18015, USA.
Abstract
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and diagnosis of mental disorders. Machine learning (ML) and artificial intelligence (AI) technologies are playing an increasingly critical role in the new era of p…
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