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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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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. |
format | Online Article Text |
id | pubmed-10594695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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