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Broad Learning Enhanced 1H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus
Joint Authors
Shen, Zhiwei
Wang, Yukai
Li, Yan
Ge, Zuhao
Zhang, Zhiyan
Zhou, Teng
Wu, Renhua
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-23
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (1H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL-SVM).
We retrospectively analysed 23 confirmed patients and 16 healthy controls, who underwent a 3.0 T magnetic resonance imaging (MRI) sequence with multivoxel 1H-MRS in our hospitals.
One hundred and seventeen metabolic features were extracted from the multivoxel 1H-MRS image.
Thirty-three metabolic features selected by the Mann-Whitney U test were considered to have a statistically significant difference (p<0.05).
However, the best accuracy achieved by conventional statistical methods using these 33 metabolic features was only 77%.
We turned to develop a support vector machine broad learning system (BL-SVM) to quantitatively analyse the metabolic features from 1H-MRS.
Although not all the individual features manifested statistics significantly, the BL-SVM could still learn to distinguish the NPSLE from the healthy controls.
The area under the receiver operating characteristic curve (AUC), the sensitivity, and the specificity of our BL-SVM in predicting NPSLE were 95%, 95.8%, and 93%, respectively, by 3-fold cross-validation.
We consequently conclude that the proposed system effectively and efficiently working on limited and noisy samples may brighten a noinvasive in vivo instrument for early diagnosis of NPSLE.
American Psychological Association (APA)
Li, Yan& Ge, Zuhao& Zhang, Zhiyan& Shen, Zhiwei& Wang, Yukai& Zhou, Teng…[et al.]. 2020. Broad Learning Enhanced 1H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1139647
Modern Language Association (MLA)
Li, Yan…[et al.]. Broad Learning Enhanced 1H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1139647
American Medical Association (AMA)
Li, Yan& Ge, Zuhao& Zhang, Zhiyan& Shen, Zhiwei& Wang, Yukai& Zhou, Teng…[et al.]. Broad Learning Enhanced 1H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1139647
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1139647