Diagnosis of Schizophrenia Based on Deep Learning Using fMRI

Schizophrenia is a brain disease that frequently occurs in young people. Early diagnosis and treatment can reduce family burdens and reduce social costs. There is no objective evaluation index for schizophrenia. In order to improve the classification effect of traditional classification methods on m...

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Autores principales:	JinChi Zheng, XiaoLan Wei, JinYi Wang, HuaSong Lin, HongRun Pan, YuQing Shi
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/6e7b1848f7f84970be0dc7b201310965
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id	oai:doaj.org-article:6e7b1848f7f84970be0dc7b201310965
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spelling	oai:doaj.org-article:6e7b1848f7f84970be0dc7b2013109652021-11-22T01:11:07ZDiagnosis of Schizophrenia Based on Deep Learning Using fMRI1748-671810.1155/2021/8437260https://doaj.org/article/6e7b1848f7f84970be0dc7b2013109652021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8437260https://doaj.org/toc/1748-6718Schizophrenia is a brain disease that frequently occurs in young people. Early diagnosis and treatment can reduce family burdens and reduce social costs. There is no objective evaluation index for schizophrenia. In order to improve the classification effect of traditional classification methods on magnetic resonance data, a method of classification of functional magnetic resonance imaging data is proposed in conjunction with the convolutional neural network algorithm. We take functional magnetic resonance imaging (fMRI) data for schizophrenia as an example, to extract effective time series from preprocessed fMRI data, and perform correlation analysis on regions of interest, using transfer learning and VGG16 net, and the functional connection between schizophrenia and healthy controls is classified. Experimental results show that the classification accuracy of fMRI based on VGG16 is up to 84.3%. On the one hand, it can improve the early diagnosis of schizophrenia, and on the other hand, it can solve the classification problem of small samples and high-dimensional data and effectively improve the generalization ability of deep learning models.JinChi ZhengXiaoLan WeiJinYi WangHuaSong LinHongRun PanYuQing ShiHindawi LimitedarticleComputer applications to medicine. Medical informaticsR858-859.7ENComputational and Mathematical Methods in Medicine, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 JinChi Zheng XiaoLan Wei JinYi Wang HuaSong Lin HongRun Pan YuQing Shi Diagnosis of Schizophrenia Based on Deep Learning Using fMRI
description	Schizophrenia is a brain disease that frequently occurs in young people. Early diagnosis and treatment can reduce family burdens and reduce social costs. There is no objective evaluation index for schizophrenia. In order to improve the classification effect of traditional classification methods on magnetic resonance data, a method of classification of functional magnetic resonance imaging data is proposed in conjunction with the convolutional neural network algorithm. We take functional magnetic resonance imaging (fMRI) data for schizophrenia as an example, to extract effective time series from preprocessed fMRI data, and perform correlation analysis on regions of interest, using transfer learning and VGG16 net, and the functional connection between schizophrenia and healthy controls is classified. Experimental results show that the classification accuracy of fMRI based on VGG16 is up to 84.3%. On the one hand, it can improve the early diagnosis of schizophrenia, and on the other hand, it can solve the classification problem of small samples and high-dimensional data and effectively improve the generalization ability of deep learning models.
format	article
author	JinChi Zheng XiaoLan Wei JinYi Wang HuaSong Lin HongRun Pan YuQing Shi
author_facet	JinChi Zheng XiaoLan Wei JinYi Wang HuaSong Lin HongRun Pan YuQing Shi
author_sort	JinChi Zheng
title	Diagnosis of Schizophrenia Based on Deep Learning Using fMRI
title_short	Diagnosis of Schizophrenia Based on Deep Learning Using fMRI
title_full	Diagnosis of Schizophrenia Based on Deep Learning Using fMRI
title_fullStr	Diagnosis of Schizophrenia Based on Deep Learning Using fMRI
title_full_unstemmed	Diagnosis of Schizophrenia Based on Deep Learning Using fMRI
title_sort	diagnosis of schizophrenia based on deep learning using fmri
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/6e7b1848f7f84970be0dc7b201310965
work_keys_str_mv	AT jinchizheng diagnosisofschizophreniabasedondeeplearningusingfmri AT xiaolanwei diagnosisofschizophreniabasedondeeplearningusingfmri AT jinyiwang diagnosisofschizophreniabasedondeeplearningusingfmri AT huasonglin diagnosisofschizophreniabasedondeeplearningusingfmri AT hongrunpan diagnosisofschizophreniabasedondeeplearningusingfmri AT yuqingshi diagnosisofschizophreniabasedondeeplearningusingfmri
_version_	1718418286419378176

Diagnosis of Schizophrenia Based on Deep Learning Using fMRI

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