AI-based approach for improving the detection of blood doping in sports - Rahman, M. R.; Bejder, J.; Bonne, T. C.; Andersen, A. B.; Huertas, J. R.; Aikin, R.; Nordsborg, B.; Maaß, W. (arXiv e-print repository, 2022)
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.