Detection of Erythropoietin in Blood to Uncover Doping in Sports using Machine Learning
Author:
Affiliation:
1. Saarland University,Germany
2. University of Copenhagen,Denmark
3. University of Granada,Spain
4. World Anti-Doping Agency,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9861038/9861040/09861084.pdf?arnumber=9861084
Reference24 articles.
1. Applying Machine Learning Techniques to Advance Anti-Doping;kelly;Eur J Sport Exerc Sci,2019
2. Hematologic passport for athletes competing in endurance sports: a feasibility study;malcovati;Haematologica,2003
3. Performance and blood monitoring in sports: The artificial intelligence evoking target testing in anti doping (AR.I.E.T.T.A.) project;manfredini;J Sports Med Phys Fitness,2011
4. Improved detection methods significantly increase the detection window for EPO microdoses
5. k-Nearest Neighbor Classification
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1. Generative Artificial Intelligence in Anti-doping Analysis in Sports;Artificial Intelligence in Sports, Movement, and Health;2024
2. Modelling Metabolism Pathways using Graph Representation Learning for Fraud Detection in Sports;2023 IEEE International Conference on Digital Health (ICDH);2023-07
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