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A Machine Learning Approach for Knee Injury Detection from Magnetic Resonance Imaging.
Mangone, Massimiliano; Diko, Anxhelo; Giuliani, Luca; Agostini, Francesco; Paoloni, Marco; Bernetti, Andrea; Santilli, Gabriele; Conti, Marco; Savina, Alessio; Iudicelli, Giovanni; Ottonello, Carlo; Santilli, Valter.
Afiliación
  • Mangone M; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Diko A; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Giuliani L; Department of Computer Science Sapienza, University of Rome, 00198 Rome, Italy.
  • Agostini F; San Salvatore Hospital, Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, Vetoio Stree, 67100 L'Aquila, Italy.
  • Paoloni M; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Bernetti A; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Santilli G; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Conti M; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Savina A; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Iudicelli G; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Ottonello C; Department of Anatomical and Histological Sciences, Legal Medicine and Orthopedics, Sapienza University, 00185 Rome, Italy.
  • Santilli V; Fisiocard Medical Centre, Via Francesco Tovaglieri 17, 00155 Rome, Italy.
Int J Environ Res Public Health ; 20(12)2023 06 06.
Article en En | MEDLINE | ID: mdl-37372646
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Calidad de Vida / Traumatismos de la Rodilla Tipo de estudio: Diagnostic_studies Aspecto: Patient_preference Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2023 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Calidad de Vida / Traumatismos de la Rodilla Tipo de estudio: Diagnostic_studies Aspecto: Patient_preference Límite: Humans Idioma: En Revista: Int J Environ Res Public Health Año: 2023 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza