Interpretable machine learning model for characterizing magnetic susceptibility-based biomarkers in first episode psychosis

Franco, Pamela; Montalba, Cristian; Caulier, Raúl; Milovic, Carlos; González, Alfonso; Ramirez, Juan; Undurraga, Juan; Salas, Rodrigo; Crossley, Nicolás; Tejos, Cristian; Uribe, Sergio

Publication:
Interpretable machine learning model for characterizing magnetic susceptibility-based biomarkers in first episode psychosis

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Interpretable machine learning model for characterizing magnetic susceptibility-based biomarkers in first episode psychosis.pdf (4.37 MB)

Date

2025

Type:

Article

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Artículos Medicina y Ciencias de la Salud

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1

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Authors

Franco, Pamela

Montalba, Cristian

Caulier, Raúl

Milovic, Carlos

González, Alfonso

Ramirez, Juan

Undurraga, Juan

Salas, Rodrigo

Crossley, Nicolás

Tejos, Cristian

item.page.doiurl

https://doi.org/10.1016/j.cmpb.2025.109067

URI

https://hdl.handle.net/11447/11211

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Acceso Abierto

Abstract

Background and purpose: Several studies have shown changes in neurochemicals within the deep-brain nuclei of patients with psychosis. These alterations indicate a dysfunction in dopamine within subcor...

Citation

Franco, P., Montalba, C., Caulier-Cisterna, R., Milovic, C., González, A., Ramirez-Mahaluf, J. P., Undurraga, J., Salas, R., Crossley, N., Tejos, C., & Uribe, S. (2025). Interpretable machine learning model for characterizing magnetic susceptibility-based biomarkers in first episode psychosis. Computer methods and programs in biomedicine, 272, 109067. https://doi.org/10.1016/j.cmpb.2025.109067

Keywords

Biomarkers , Artificial intelligence for medical imaging , Interpretable machine learning , Magnetic resonance imaging , Quantitative susceptibility mapping

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