Leveraging Artificial Intelligence and Synthetic Data Derivatives for Spine Surgery Research.

Greenberg, Jacob K; Landman, Joshua M; Kelly, Michael P; Pennicooke, Brenton H; Molina, Camilo A; Foraker, Randi E; Ray, Wilson Z

Greenberg, Jacob K; Landman, Joshua M; Kelly, Michael P; Pennicooke, Brenton H; Molina, Camilo A; Foraker, Randi E; Ray, Wilson Z.

Afiliación

Greenberg JK; Departments of Neurological Surgery, Medicine and Orthopaedic Surgery, Washington University School of Medicine in St Louis, St Louis, MO, USA.
Landman JM; Departments of Neurological Surgery, Medicine and Orthopaedic Surgery, Washington University School of Medicine in St Louis, St Louis, MO, USA.
Kelly MP; Orthopaedic Surgery, Washington University, St Louis, MO, USA.
Pennicooke BH; Departments of Neurological Surgery, Medicine and Orthopaedic Surgery, Washington University School of Medicine in St Louis, St Louis, MO, USA.
Molina CA; Departments of Neurological Surgery, Medicine and Orthopaedic Surgery, Washington University School of Medicine in St Louis, St Louis, MO, USA.
Foraker RE; Orthopaedic Surgery, Washington University, St Louis, MO, USA.
Ray WZ; Departments of Neurological Surgery, Medicine and Orthopaedic Surgery, Washington University School of Medicine in St Louis, St Louis, MO, USA.

Global Spine J ; 13(8): 2409-2421, 2023 Oct.

Article en En | MEDLINE | ID: mdl-35373623

Palabras clave

artificial intelligence; electronic health records; machine learning; medical informatics; spine surgery; synthetic data derivatives; treatment outcome

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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Global Spine J Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

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