AI-based approach for improving the detection of blood doping in sports

(KI-basierter Ansatz zur Verbesserung der Erkennung von Blutdoping im Sport)

Sports officials around the world are facing incredible challenges due to the unfair means of practices performed by the athletes to improve their performance in the game. It includes the intake of hormonal based drugs or transfusion of blood to increase their strength and the result of their training. However, the current direct test of detection of these cases includes the laboratory-based method, which is limited because of the cost factors, availability of medical experts, etc. This leads us to seek for indirect tests. With the growing interest of Artificial Intelligence in healthcare, it is important to propose an algorithm based on blood parameters to improve decision making. In this paper, we proposed a statistical and machine learning-based approach to identify the presence of doping substance rhEPO in blood samples.
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Bibliographische Detailangaben
Schlagworte:
Notationen:Biowissenschaften und Sportmedizin Naturwissenschaften und Technik
Tagging:maschinelles Lernen WADA künstliche Intelligenz
Veröffentlicht in:arXiv e-print repository
Sprache:Englisch
Veröffentlicht: 2022
Online-Zugang:https://doi.org/10.48550/arXiv.2203.00001
Heft:preprint
Dokumentenarten:Forschungsergebnis
Level:hoch