Explainable Multi-Modal and Local Approaches to Modelling Injuries in Sports Data-Reference-Cited by-同舟云学术

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Explainable Multi-Modal and Local Approaches to Modelling Injuries in Sports Data

Published:2023-12-04 Issue: Volume:1050 Page:949-957
ISSN:
Container-title:2023 IEEE International Conference on Data Mining Workshops (ICDMW)
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Author:

Hudson Dan¹,Hartigh Ruud. J. R. Den²,Meerhoff L. Rens A.³,Atzmueller Martin⁴

Affiliation:

1. Osnabrück University,Semantic Information Systems Group,Osnabrück,Germany

2. University of Groningen,Faculty of Behavioral and Social Sciences,Groningen,The Netherlands

3. Leiden University,Leiden Institute of Advanced Computer Sciences (LIACS),Leiden,The Netherlands

4. Semantic Information Systems Group Osnabrück University,German Research Center for Artificial Intelligence (DFKI),Osnabrück,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10411504/10411508/10411621.pdf?arnumber=10411621

Reference46 articles.

1. A Machine Learning Approach to Assess Injury Risk in Elite Youth Football Players

2. Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players

3. Injury Prediction in Competitive Runners With Machine Learning

4. A Machine-Learning Approach to Measure the Anterior Cruciate Ligament Injury Risk in Female Basketball Players

5. Eccentric Hamstring Strength and Hamstring Injury Risk in Australian Footballers

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