Systematic review of machine-learning models in orthopaedic trauma: an overview and quality assessment of 45 studies

Aims: Machine-learning (ML) prediction models in orthopaedic trauma hold great promise in assisting clinicians in various tasks, such as personalized risk stratification. However, an overview of current applications and critical appraisal to peer-reviewed guidelines is lacking. The objectives of thi...

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Detalhes bibliográficos

Principais autores:	Hidde Dijkstra, Anouk van de Kuit, Tom de Groot, Olga Canta, Olivier Q. Groot, Jacobien H. Oosterhoff, Job N. Doornberg, On behalf of the Machine Learning Consortium
Formato:	Artigo
Idioma:	Inglês
Publicado em:	The British Editorial Society of Bone & Joint Surgery 2024-01-01
coleção:	Bone & Joint Open
Assuntos:	systematic review machine learning orthopaedic trauma quality assessment clinicians hip fracture prognosis orthopaedic trauma surgery logistic regression techniques imaging studies anterior cruciate ligament revision surgery elective orthopaedic surgery
Acesso em linha:	https://online.boneandjoint.org.uk/doi/epdf/10.1302/2633-1462.51.BJO-2023-0095.R1
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