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機械学習を用いた術中MEPモニタリング施行症例における術後麻痺予測のモデルの構築

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機械学習を用いた術中MEPモニタリング施行症例における術後麻痺予測のモデルの構築

Material type
文書・図像類
Author
油野, 岳夫ほか
Publisher
-
Publication date
2020-04-18
Material Format
Digital
Capacity, size, etc.
-
NDC
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Notes on use

Note (General)：

金沢大学附属病院術中運動誘発電位(MEP)モニタリングは、術後麻痺回避のため錐体路機能を術中に評価する。しかし、MEPモニタリングは様々な要因により影響を受けるため、術後麻痺の予測精度が高くないという問題がある。本研究では、機械学習を用いて、MEPモニタリング下での脳腫瘍摘出症例の術後麻痺予測モデル...

Related materials as well as pre- and post-revision versions

https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-19H00448/

https://kaken.nii.ac.jp/report/KAKENHI-PROJECT-19H00448/19H00448seika/

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  • Kanazawa University Repository for Academic Resources

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Digital

Material Type
文書・図像類
Title
機械学習を用いた術中MEPモニタリング施行症例における術後麻痺予測のモデルの構築
Author/Editor
油野, 岳夫
Yuno, Takeo
Author Heading
油野, 岳夫
Yuno, Takeo
Publication Date
2020-04-18
Publication Date (W3CDTF)
2020-04-18
Periodical title
令和1(2019)年度 科学研究費補助金 奨励研究 研究成果報告書 = 2019 Fiscal Year Final Research Report
No. or year of volume/issue
2019
Volume
2019
Pages
3p.-