Literature DB >> 33874846

Machine learning in sports science: challenges and opportunities.

Chris Richter1, Martin O'Reilly2, Eamonn Delahunt2.   

Abstract

Year:  2021        PMID： 33874846     DOI： 10.1080/14763141.2021.1910334

Source DB:  PubMed          Journal:  Sports Biomech        ISSN： 1476-3141            Impact factor:   2.832


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  4 in total

1.  Predicting surgical outcomes for chronic exertional compartment syndrome using a machine learning framework with embedded trust by interrogation strategies.

Authors:  Andrew Houston; Georgina Cosma; Phillipa Turner; Alexander Bennett
Journal:  Sci Rep       Date:  2021-12-20       Impact factor: 4.379

2.  A machine learning approach to identify risk factors for running-related injuries: study protocol for a prospective longitudinal cohort trial.

Authors:  A L Rahlf; T Hoenig; J Stürznickel; K Cremans; D Fohrmann; A Sanchez-Alvarado; T Rolvien; K Hollander
Journal:  BMC Sports Sci Med Rehabil       Date:  2022-04-26

3.  Construction of Women's All-Around Speed Skating Event Performance Prediction Model and Competition Strategy Analysis Based on Machine Learning Algorithms.

Authors:  Meng Liu; Yan Chen; Zhenxiang Guo; Kaixiang Zhou; Limingfei Zhou; Haoyang Liu; Dapeng Bao; Junhong Zhou
Journal:  Front Psychol       Date:  2022-07-12

4.  Predicting ACL Injury Using Machine Learning on Data From an Extensive Screening Test Battery of 880 Female Elite Athletes.

Authors:  Susanne Jauhiainen; Jukka-Pekka Kauppi; Tron Krosshaug; Roald Bahr; Julia Bartsch; Sami Äyrämö
Journal:  Am J Sports Med       Date:  2022-08-19       Impact factor: 7.010
  4 in total

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