A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors

Predictive modeling could contribute to precision psychiatry. However, our study underlines the difficulty in selecting variables with sufficient impact on complex outcomes.

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Publication Details

Journal
Psychiatric Genetics
Published
2025-02-26
DOI
https://doi.org/10.1097/ypg.0000000000000379
Citations
2
Primary Topic
Pharmacogenetics and Drug Metabolism
Type
article
Field-Weighted Citation Impact
3.11
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article

A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors

Stuart Montgomery, Joseph Zohar, Concetta Crisafulli, Alessandro Serretti et al.
2 citations
Psychiatric Genetics
Pharmacogenetics and Drug Metabolism
3.11
article

A machine learning approach to predict treatment efficacy and adverse effects in major depression using CYP2C19 and clinical-environmental predictors

Stuart Montgomery, Joseph Zohar, Concetta Crisafulli, Alessandro Serretti, Panagiotis P. Ferentinos, Raffaella Zanardi, Cristina Colombo, Chiara Fabbri, Dan Rujescu, Siegfried Kasper, Daniel Souery, Gianluigi Forloni, Marco Calabrò, Diego Albani, J. Mendlewicz, Diana De Ronchi
article en
2 citations

Abstract

Predictive modeling could contribute to precision psychiatry. However, our study underlines the difficulty in selecting variables with sufficient impact on complex outcomes.

Psychiatric GeneticsVol. 35(2)
University of Messina (IT), Université Libre de Bruxelles (BE), Vita-Salute San Raffaele University (IT), Tel Aviv University (IL), Mario Negri Institute for Pharmacological Research (IT), Università degli Studi di Enna Kore (IT), Sheba Medical Center (IL), Oasi Maria SS (IT), IRCCS Ospedale San Raffaele (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT), Centro Neurolesi Bonino Pulejo (IT), Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele (IT), Imperial College London (GB), Medical University of Vienna (AT), University of Bologna (IT)
Good health and well-being
Openalex Percentile: Top 12%
Pharmacogenetics and Drug Metabolism
3.11
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