Poster 179: Unsupervised Machine Learning to Identify Clinically Meaningful Subgroups in Patients Undergoing Arthroscopic Rotator Cuff Repair

OBJECTIVES: Rotator cuff tears are estimated to affect 20.7% of the population, with the prevalence increasing with age. Surgery is indicated after non-response to nonoperative treatment, with arthroscopic rotator cuff repair (ARCR) as the current standard for full thickness tears. Clinically signif...

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Detalles Bibliográficos
Autores principales: Lu, Yining, Berlinberg, Elyse, Patel, Harsh, Rice, Morgan, Gamsarian, Vahram, Hevesi, Mario, Mirle, Vikranth, Yanke, Adam, Cole, Brian, Verma, Nikhil, Group, Forsythe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392385/
http://dx.doi.org/10.1177/2325967123S00165

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10392385/
http://dx.doi.org/10.1177/2325967123S00165

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