Machine Learning Outperforms Logistic Regression Analysis to Predict Next-Season NHL Player Injury: An Analysis of 2322 Players From 2007 to 2017

BACKGROUND: The opportunity to quantitatively predict next-season injury risk in the National Hockey League (NHL) has become a reality with the advent of advanced computational processors and machine learning (ML) architecture. Unlike static regression analyses that provide a momentary prediction, M...

Full beskrivning

Sparad:
Bibliografiska uppgifter
I publikationen:Orthop J Sports Med
Huvudupphovsmän: Luu, Bryan C., Wright, Audrey L., Haeberle, Heather S., Karnuta, Jaret M., Schickendantz, Mark S., Makhni, Eric C., Nwachukwu, Benedict U., Williams, Riley J., Ramkumar, Prem N.
Materialtyp: Artigo
Språk:Inglês
Publicerad: SAGE Publications 2020
Ämnen:
Article
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC7522848/
https://ncbi.nlm.nih.gov/pubmed/33029545
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/2325967120953404
Taggar: Lägg till en tagg
Inga taggar, Lägg till första taggen!

Liknande verk