The potential of precision psychiatry: What is in reach? - Kölner UniversitätsPublikationsServer

Kambeitz-Ilankovic, Lana ORCID: 0000-0002-8218-0425, Koutsouleris, Nikolaos and Upthegrove, Rachel ORCID: 0000-0001-8204-5103 (2022). The potential of precision psychiatry: What is in reach? Br. J. Psychiatry, 220 (4). S. 175 - 179. CAMBRIDGE: CAMBRIDGE UNIV PRESS. ISSN 1472-1465

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DOI:10.1192/bjp.2022.23

Abstract

Progress in developing personalised care for mental disorders is supported by numerous proof-of-concept machine learning studies in the area of risk assessment, diagnostics and precision prescribing. Most of these studies primarily use clinical data, but models might benefit from additional neuroimaging, blood and genetic data to improve accuracy. Combined, multimodal models might offer potential for stratification of patients for treatment. Clinical implementation of machine learning is impeded by a lack of wider generalisability, with efforts primarily focused on psychosis and dementia. Studies across all diagnostic groups should work to test the robustness of machine learning models, which is an essential first step to clinical implementation, and then move to prospective clinical validation. Models need to exceed clinicians' heuristics to be useful, and safe, in routine decision-making. Engagement of clinicians, researchers and patients in digitalisation and 'big data' approaches are vital to allow the generation and accessibility of large, longitudinal, prospective data needed for precision psychiatry to be applied into real-world psychiatric care.

Item Type:

Journal Article

Creators:

Creators	Email	ORCID	ORCID Put Code
Kambeitz-Ilankovic, Lana	UNSPECIFIED	orcid.org/0000-0002-8218-0425	UNSPECIFIED
Koutsouleris, Nikolaos	UNSPECIFIED	UNSPECIFIED	UNSPECIFIED
Upthegrove, Rachel	UNSPECIFIED	orcid.org/0000-0001-8204-5103	UNSPECIFIED