Detection of Erythropoietin in Blood to Uncover Doping in Sports using Machine Learning

Author:

Rahman Maxx Richard1,Bejder Jacob2,Bonne Thomas Christian2,Andersen Andreas Breenfeldt2,Huertas Jesus Rodriguez3,Aikin Reid4,Nordsborg Nikolai Baastrup2,Maass Wolfgang1

Affiliation:

1. Saarland University,Germany

2. University of Copenhagen,Denmark

3. University of Granada,Spain

4. World Anti-Doping Agency,Canada

Publisher

IEEE

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

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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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