论文标题
基于AI的方法来改善运动中血液掺杂的检测
AI-based approach for improving the detection of blood doping in sports
论文作者
论文摘要
全球体育官员面临着令人难以置信的挑战，这是由于运动员在比赛中提高其表现的不公平练习方式。它包括摄入基于激素的药物或输血以增加其强度和训练的结果。但是，当前对这些病例检测的直接测试包括基于实验室的方法，由于成本因素，医疗专家的可用性等，这受到限制。这导致我们寻求间接测试。随着人工智能对医疗保健的日益兴趣，重要的是提出基于血液参数的算法以改善决策。在本文中，我们提出了一种基于统计和机器学习的方法，以鉴定血样中掺杂物质Rhepo的存在。
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.
