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AI MSK clinical applications: orthopedic implants.
Yi, Paul H; Mutasa, Simukayi; Fritz, Jan.
Afiliação
  • Yi PH; University of Maryland Intelligent Imaging (UMII) Center, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA. pyi@som.umaryland.edu.
  • Mutasa S; Center for Artificial Intelligence in Diagnostic Medicine (CAIDM) and Department of Radiological Sciences, University of California, Irvine, Irvine, CA, USA.
  • Fritz J; Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.
Skeletal Radiol ; 51(2): 305-313, 2022 Feb.
Article em En | MEDLINE | ID: mdl-34350476
Artificial intelligence (AI) and deep learning have multiple potential uses in aiding the musculoskeletal radiologist in the radiological evaluation of orthopedic implants. These include identification of implants, characterization of implants according to anatomic type, identification of specific implant models, and evaluation of implants for positioning and complications. In addition, natural language processing (NLP) can aid in the acquisition of clinical information from the medical record that can help with tasks like prepopulating radiology reports. Several proof-of-concept works have been published in the literature describing the application of deep learning toward these various tasks, with performance comparable to that of expert musculoskeletal radiologists. Although much work remains to bring these proof-of-concept algorithms into clinical deployment, AI has tremendous potential toward automating these tasks, thereby augmenting the musculoskeletal radiologist.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ortopedia / Sistema Musculoesquelético Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ortopedia / Sistema Musculoesquelético Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article