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Functional assessment using 3D movement analysis can better predict health-related quality of life outcomes in patients with adult spinal deformity: a machine learning approach.

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第一作者： Elio,Mekhael

第一单位： Faculty of Medicine, Saint Joseph University of Beirut, Beirut, Lebanon.

作者： Elio,Mekhael ^[1] ; Rami,El Rachkidi ^[1] ; Renee Maria,Saliby ^[1] ; Nabil,Nassim ^[1] ; Karl,Semaan ^[1] ; Abir,Massaad ^[1] ; Mohamad,Karam ^[1] ; Maria,Saade ^[1] ; Elma,Ayoub ^[1] ; Ali,Rteil ^[1] ; Elena,Jaber ^[1] ; Celine,Chaaya ^[1] ; Julien,Abi Nahed ^[2] ; Ismat,Ghanem ^[1] ; Ayman,Assi ^[3]

作者单位： Faculty of Medicine, Saint Joseph University of Beirut, Beirut, Lebanon. ^[1] Technology Innovation Unit, Hamad Medical Corporation, Doha, Qatar. ^[2] Faculty of Medicine, Saint Joseph University of Beirut, Beirut, Lebanon.;Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers ParisTech, Angers, France. ^[3]

关键词 3D movement analysis adult spinal deformity follow-up functional assessment gait health-related quality of life machine learning

DOI 10.3389/fsurg.2023.1166734

PMID 37206356

发布时间 2023-05-22

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Frontiers in surgery

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Frontiers in surgery

2023年10卷

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Functional assessment using 3D movement analysis can better predict health-related quality of life outcomes in patients with adult spinal deformity: a machine learning approach.

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Functional assessment using 3D movement analysis can better predict health-related quality of life outcomes in patients with adult spinal deformity: a machine learning approach.

Frontiers in surgery

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Frontiers in surgery

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