ArticleFrontiers in physiology2018
ABPS: An R Package for Calculating the Abnormal Blood Profile Score.
Article in Frontiers in physiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- mRNA Biomarkers in Dried Blood Spots May Improve Detection of Autologous Blood Micro-Transfusions Using an Individualized Approach.Drug testing and analysis · 2025Trial
- Chinese Herbal Medicine Significantly Impacts the Haematological Variables of the Athlete Biological Passport.International journal of environmental research and public health · 2021Trial
- Does blood tube filling influence the Athlete Biological Passport variables?Clinical chemistry and laboratory medicine · 2025Article
- Athlete biological passport: longitudinal biomarkers and statistics in the fight against doping.Arhiv za higijenu rada i toksikologiju · 2024Review
- Intermittent not continuous hypoxia provoked haematological adaptations in healthy seniors: hypoxic pattern may hold the key.European journal of applied physiology · 2020Article
- Prevalence Estimate of Blood Doping in Elite Track and Field Athletes During Two Major International Events.Frontiers in physiology · 2020Article
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Authors and funding
2 authors.
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Abstract
The Abnormal Blood Profile Score (ABPS) is used to identify blood doping in sport. It combines seven hematological markers, including hemoglobin level, reticulocytes percent, and haematocrit level, using two different machine learning algorithms in order to create a single score that has a better ability to identify doping than each parameter taken alone. The resulting score allows the detection of several types of doping using a single score and is part of the current Athlete Biological Passport program managed by World Anti-Doping Agency (WADA). We describe ≪ ABPS ≫, an R package that allows the calculation of this score. This is the first software implementation calculating this score that is released publicly. The package also contains functions to calculate the OFF-score (another score used for detection of doping), as well as several test datasets. The package is useful for laboratories conducting anti-doping analyses and for researchers working on anti-doping research projects. In particular, it has been successfully used in projects estimating the prevalence of blood doping.
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