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

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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Bibliographic Details
Subjects:
Notations:biological and medical sciences technical and natural sciences
Tagging:maschinelles Lernen WADA künstliche Intelligenz
Published in:arXiv e-print repository
Language:English
Published: 2022
Online Access:https://doi.org/10.48550/arXiv.2203.00001
Issue:preprint
Document types:research paper
Level:advanced