Cargando…
Machine Learning Does Not Improve Humeral Torsion Prediction Compared to Regression in Baseball Pitchers
BACKGROUND: Humeral torsion is an important osseous adaptation in throwing athletes that can contribute to arm injuries. Currently there are no cheap and easy to use clinical tools to measure humeral torsion, inhibiting clinical assessment. Models with low error and “good” calibration slope may be h...
Autores principales: | Bullock, Garrett S, Thigpen, Charles A, Collins, Gary S, Arden, Nigel K, Noonan, Thomas K, Kissenberth, Michael J, Shanley, Ellen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
NASMI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8975570/ https://www.ncbi.nlm.nih.gov/pubmed/35391864 http://dx.doi.org/10.26603/001c.32380 |
Ejemplares similares
-
Development of an Injury Burden Prediction Model in Professional Baseball Pitchers
por: Bullock, Garrett, et al.
Publicado: (2022) -
Humeral Torsion as a Risk Factor for Shoulder and Elbow Injury in Professional Baseball Pitchers
por: Noonan, Thomas J., et al.
Publicado: (2015) -
Professional Pitchers with GIRD Display Greater Dominant Humeral Retrotorsion than Pitchers with Normal ROM
por: Noonan, Thomas J., et al.
Publicado: (2013) -
Elbow Injuries Among MLB Pitchers Increased During Covid-19 Disrupted Season, But Not Other Baseball Injuries
por: Martin, Chelsea, et al.
Publicado: (2023) -
Using Stress Ultrasonography to Understand the Risk of UCL Injury Among Professional Baseball Pitchers Based on Ligament Morphology and Dynamic Abnormalities
por: Shanley, Ellen, et al.
Publicado: (2018)