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Natural language processing: using artificial intelligence to understand human language in orthopedics.
Pruneski, James A; Pareek, Ayoosh; Nwachukwu, Benedict U; Martin, R Kyle; Kelly, Bryan T; Karlsson, Jón; Pearle, Andrew D; Kiapour, Ata M; Williams, Riley J.
Afiliación
  • Pruneski JA; Department of Orthopedic Surgery, Boston Children's Hospital, Boston, MA, USA.
  • Pareek A; Sports Medicine and Shoulder Service, Hospital for Special Surgery, 535 East 70th Street, New York, NY, USA. ayooshp@gmail.com.
  • Nwachukwu BU; Department of Orthopaedics, Sahlgrenska University Hospital, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden. ayooshp@gmail.com.
  • Martin RK; Sports Medicine and Shoulder Service, Hospital for Special Surgery, 535 East 70th Street, New York, NY, USA.
  • Kelly BT; Department of Orthopedic Surgery, University of Minnesota, Minneapolis, MN, USA.
  • Karlsson J; Sports Medicine and Shoulder Service, Hospital for Special Surgery, 535 East 70th Street, New York, NY, USA.
  • Pearle AD; Department of Orthopaedics, Sahlgrenska University Hospital, Sahlgrenska Academy, Gothenburg University, Gothenburg, Sweden.
  • Kiapour AM; Sports Medicine and Shoulder Service, Hospital for Special Surgery, 535 East 70th Street, New York, NY, USA.
  • Williams RJ; Department of Orthopedic Surgery, Boston Children's Hospital, Boston, MA, USA.
Knee Surg Sports Traumatol Arthrosc ; 31(4): 1203-1211, 2023 Apr.
Article en En | MEDLINE | ID: mdl-36477347
ABSTRACT
Natural language processing (NLP) describes the broad field of artificial intelligence by which computers are trained to understand and generate human language. Within healthcare research, NLP is commonly used for variable extraction and classification/cohort identification tasks. While these tools are becoming increasingly popular and available as both open-source and commercial products, there is a paucity of the literature within the orthopedic space describing the key tasks within these powerful pipelines. Curation and navigation of the electronic medical record are becoming increasingly onerous, and it is important for physicians and other healthcare professionals to understand potential methods of harnessing this large data resource. The purpose of this study is to provide an overview of the tasks required to develop an NLP pipeline for orthopedic research and present recent examples of successful implementations.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Ortopedia / Procedimientos Ortopédicos Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Knee Surg Sports Traumatol Arthrosc Asunto de la revista: MEDICINA ESPORTIVA / TRAUMATOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Ortopedia / Procedimientos Ortopédicos Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Knee Surg Sports Traumatol Arthrosc Asunto de la revista: MEDICINA ESPORTIVA / TRAUMATOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos