A primer on the use of machine learning to distil knowledge from data in biological psychiatry.

Stephen J Glatt, Isabelle Bichindaritz, Asif Salekin, Jiahui Hou, Junfang Chen, Mehmet Eren Ahsen, Xiaoyu Men, Samar S M Elsheikh, Malgorzata Maciukiewicz, Michelle M Barnett, Kristin K Nicodemus, Andreas Meyer-Lindenberg, Stephen V Faraone, Murray J Cairns, Ping-I Lin, Thomas P Quinn, Jonathan L Hess, Gaurav Pandey, Anne-Christin Hauschild, Yannis J Trakadis, Emanuel Schwarz, Daniel J Müller, Victoria S Marshe, Eric J Barnett, Yanli Zhang-James, Han Cao, Michael S Breen

Journal: Molecular psychiatry 2024;29(2):387-401

PMID: 38177352

Abstract

Applications of machine learning in the biomedical sciences are growing rapidly. This growth has been spurred by diverse cross-institutional and interdisciplinary collaborations, public availability of large datasets, an increase in the accessibility of analytic routines, and the availability of powerful computing resources. With this increased access and exposure to machine learning comes a responsibility for education and a deeper understanding of its bases and bounds, borne equally by data scientists seeking to ply their analytic wares in medical research and by biomedical scientists seeking to harness such methods to glean knowledge from data. This article provides an accessible and critical review of machine learning for a biomedically informed audience, as well as its applications in psychiatry. The review covers definitions and expositions of commonly used machine learning methods, and historical trends of their use in psychiatry. We also provide a set of standards, namely Guidelines for REporting Machine Learning Investigations in Neuropsychiatry (GREMLIN), for designing and reporting studies that use machine learning as a primary data-analysis approach. Lastly, we propose the establishment of the Machine Learning in Psychiatry (MLPsych) Consortium, enumerate its objectives, and identify areas of opportunity for future applications of machine learning in biological psychiatry. This review serves as a cautiously optimistic primer on machine learning for those on the precipice as they prepare to dive into the field, either as methodological practitioners or well-informed consumers.

© 2023. The Author(s), under exclusive licence to Springer Nature Limited.

Address: Applied Artificial Intelligence Institute (A2I2), Burwood, VIC, 3125, Australia.; Department of Psychiatry and Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA.; Institute of Medical Science, University of Toronto, Toronto, ON, M5S 1A1, Canada.; Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5S 1A1, Canada.; School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, 2308, Australia.; Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW, 2308, Australia.; Department of Medical Informatics, Medical University Center Göttingen, Göttingen, Lower Saxony, 37075, Germany.; Hospital Zurich, University of Zurich, Zurich, 8091, Switzerland.; Department of Rheumatology and Immunology, University Hospital Bern, Bern, 3010, Switzerland.; Department for Biomedical Research (DBMR), University of Bern, Bern, 3010, Switzerland.; Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5S 1A1, Canada.; Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5S 1A1, Canada.; Department of Pharmacology and Toxicology, University of Toronto, Toronto, ON, M5S 1A1, Canada.; Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Baden-Württemberg, J5 68159, Germany.; Department Human Genetics, McGill University Health Centre, Montreal, QC, H4A 3J1, Canada.; Psychiatry, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.; Department of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA.; Department of Business Administration, Gies College of Business, University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA.; Department of Biomedical and Translational Sciences, Carle-Illinois School of Medicine, University of Illinois at Urbana-Champaign, Champaign, IL, 61820, USA.; Department of Psychiatry and Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA.; Department of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA.; Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, 13244, USA.; Discipline of Psychiatry and Mental Health, University of New South Wales, Sydney, NSW, 2052, Australia.; Mental Health Research Unit, South Western Sydney Local Health District, Liverpool, NSW, 2170, Australia.; Usher Institute, University of Edinburgh, Edinburgh, EH8 9YL, UK.; Clinical Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Baden-Württemberg, J5 68159, Germany.; Biomedical and Health Informatics/Computer Science Department, State University of New York at Oswego, Oswego, NY, 13126, USA.; Intelligent Bio Systems Lab, State University of New York at Oswego, Oswego, NY, 13126, USA.; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.; Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5S 1A1, Canada.; Department of Psychiatry, University of Toronto, Toronto, ON, M5S 1A1, Canada.; Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg, 97080, Germany.; Department of Psychiatry and Behavioral Sciences, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA. [email protected].; Department of Neuroscience and Physiology, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA. [email protected].; Department of Public Health and Preventive Medicine, Norton College of Medicine at SUNY Upstate Medical University, Syracuse, NY, 13210, USA. [email protected].

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