Application of Machine Learning Algorithms to Predict Clinically Meaningful Improvement After Arthroscopic Anterior Cruciate Ligament Reconstruction

BACKGROUND: Understanding specific risk profiles for each patient and their propensity to experience clinically meaningful improvement after anterior cruciate ligament reconstruction (ACLR) is important for preoperative patient counseling and management of expectations. PURPOSE: To develop machine l...

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Detalles Bibliográficos
Autores principales: Kunze, Kyle N., Polce, Evan M., Ranawat, Anil S., Randsborg, Per-Henrik, Williams, Riley J., Allen, Answorth A., Nwachukwu, Benedict U., Pearle, Andrew, Stein, Beth S., Dines, David, Kelly, Anne, Kelly, Bryan, Rose, Howard, Maynard, Michael, Strickland, Sabrina, Coleman, Struan, Hannafin, Jo, MacGillivray, John, Marx, Robert, Warren, Russell, Rodeo, Scott, Fealy, Stephen, O’Brien, Stephen, Wickiewicz, Thomas, Dines, Joshua S., Cordasco, Frank, Altcheck, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521431/
https://www.ncbi.nlm.nih.gov/pubmed/34671691
http://dx.doi.org/10.1177/23259671211046575

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8521431/
https://www.ncbi.nlm.nih.gov/pubmed/34671691
http://dx.doi.org/10.1177/23259671211046575

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