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Artificial intelligence applications in psychoradiology

One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness, prediction of prognosis before treatment, and guidance for selection of effective...

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Detalles Bibliográficos
Autores principales: Li, Fei, Sun, Huaiqiang, Biswal, Bharat B, Sweeney, John A, Gong, Qiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594695/
https://www.ncbi.nlm.nih.gov/pubmed/37881257
http://dx.doi.org/10.1093/psyrad/kkab009
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author Li, Fei
Sun, Huaiqiang
Biswal, Bharat B
Sweeney, John A
Gong, Qiyong
author_facet Li, Fei
Sun, Huaiqiang
Biswal, Bharat B
Sweeney, John A
Gong, Qiyong
author_sort Li, Fei
collection PubMed
description One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness, prediction of prognosis before treatment, and guidance for selection of effective treatments that target patient-relevant pathophysiological features. This is the primary aim of the field of Psychoradiology. Using databases collected from large samples at multiple centers, sophisticated artificial intelligence (AI) algorithms may be used to develop clinically useful image analysis pipelines that can help physicians diagnose, predict, and make treatment decisions. In this review, we selectively summarize psychoradiological research using magnetic resonance imaging of the brain to explore the neural mechanism of psychiatric disorders, and outline progress and the path forward for the combination of psychoradiology and AI for complementing clinical examinations in patients with psychiatric disorders, as well as limitations in the application of AI that should be considered in future translational research.
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spelling pubmed-105946952023-10-25 Artificial intelligence applications in psychoradiology Li, Fei Sun, Huaiqiang Biswal, Bharat B Sweeney, John A Gong, Qiyong Psychoradiology Review One important challenge in psychiatric research is to translate findings from brain imaging research studies that identified brain alterations in patient groups into an accurate diagnosis at an early stage of illness, prediction of prognosis before treatment, and guidance for selection of effective treatments that target patient-relevant pathophysiological features. This is the primary aim of the field of Psychoradiology. Using databases collected from large samples at multiple centers, sophisticated artificial intelligence (AI) algorithms may be used to develop clinically useful image analysis pipelines that can help physicians diagnose, predict, and make treatment decisions. In this review, we selectively summarize psychoradiological research using magnetic resonance imaging of the brain to explore the neural mechanism of psychiatric disorders, and outline progress and the path forward for the combination of psychoradiology and AI for complementing clinical examinations in patients with psychiatric disorders, as well as limitations in the application of AI that should be considered in future translational research. Oxford University Press 2021-07-02 /pmc/articles/PMC10594695/ /pubmed/37881257 http://dx.doi.org/10.1093/psyrad/kkab009 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of West China School of Medicine/West China Hospital (WCSM/WCH) of Sichuan University. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review
Li, Fei
Sun, Huaiqiang
Biswal, Bharat B
Sweeney, John A
Gong, Qiyong
Artificial intelligence applications in psychoradiology
title Artificial intelligence applications in psychoradiology
title_full Artificial intelligence applications in psychoradiology
title_fullStr Artificial intelligence applications in psychoradiology
title_full_unstemmed Artificial intelligence applications in psychoradiology
title_short Artificial intelligence applications in psychoradiology
title_sort artificial intelligence applications in psychoradiology
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594695/
https://www.ncbi.nlm.nih.gov/pubmed/37881257
http://dx.doi.org/10.1093/psyrad/kkab009
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