Limitations of Hematological Profiling for Autologous Blood Doping Detection: A Controlled Trial and Diagnostic Accuracy Evaluation of Machine Learning Models
This controlled trial demonstrates that current hematological profiling and machine learning models fail to detect optimized autologous blood doping at mandatory 99% specificity thresholds due to rapid physiological compensation and overlapping variance, necessitating a shift toward direct molecular detection or absolute total hemoglobin mass tracking.
Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
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