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Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression
https://oist.repo.nii.ac.jp/records/439
https://oist.repo.nii.ac.jp/records/439dfdb5ab1-be6d-4999-a3a9-e2827d76a4cb
名前 / ファイル | ライセンス | アクション |
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journal.pone.0179638 (7.8 MB)
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Creative Commons Attribution 4.0 International
(http://creativecommons.org/licenses/by/4.0/) |
Item type | 学術雑誌論文 / Journal Article(1) | |||||
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公開日 | 2018-07-23 | |||||
タイトル | ||||||
言語 | en | |||||
タイトル | Prediction of clinical depression scores and detection of changes in whole-brain using resting-state functional MRI data with partial least squares regression | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
著者(英) |
Yoshida, Kosuke
× Yoshida, Kosuke× Shimizu, Yu× Yoshimoto, Junichiro× Takamura, Masahiro× Okada, Go× Okamoto, Yasumasa× Yamawaki, Shigeto× Doya, Kenji |
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書誌情報 |
en : PLoS ONE 巻 12, 号 7, p. e0179638, 発行日 2017-07-12 |
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抄録 | ||||||
内容記述タイプ | Other | |||||
内容記述 | In diagnostic applications of statistical machine learning methods to brain imaging data, common problems include data high-dimensionality and co-linearity, which often cause over-fitting and instability. To overcome these problems, we applied partial least squares (PLS) regression to resting-state functional magnetic resonance imaging (rs-fMRI) data, creating a low-dimensional representation that relates symptoms to brain activity and that predicts clinical measures. Our experimental results, based upon data from clinically depressed patients and healthy controls, demonstrated that PLS and its kernel variants provided significantly better prediction of clinical measures than ordinary linear regression. Subsequent classification using predicted clinical scores distinguished depressed patients from healthy controls with 80% accuracy. Moreover, loading vectors for latent variables enabled us to identify brain regions relevant to depression, including the default mode network, the right superior frontal gyrus, and the superior motor area. | |||||
出版者 | ||||||
出版者 | Public Library of Science | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1932-6203 | |||||
PubMed番号 | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | PMID | |||||
関連識別子 | info:pmid/28700672 | |||||
DOI | ||||||
関連タイプ | isIdenticalTo | |||||
識別子タイプ | DOI | |||||
関連識別子 | info:doi/10.1371/journal.pone.0179638 | |||||
権利 | ||||||
権利情報 | © 2017 Yoshida et al. | |||||
関連サイト | ||||||
識別子タイプ | URI | |||||
関連識別子 | http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0179638 | |||||
著者版フラグ | ||||||
出版タイプ | VoR | |||||
出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 |