Engl, E., Smittenaar, P. and Sgaier, S.K. (2019) Identifying Population Segments for Effective Intervention Design and Targeting Using Unsupervised Machine Learning: An End-to-End Guide. Gates Open Research, 3, Article 1503.
https://doi.org/10.12688/gatesopenres.13029.1

has been cited by the following article:

• TITLE: The Hidden Epidemic: Doping in Gyms and the Role of AI in Preventive Health

  AUTHORS: Damaris Were Ogama

  KEYWORDS: Doping, Gym, Artificial Intelligence

  JOURNAL NAME: Health, Vol.17 No.7, July 25, 2025

  ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously increasing among recreational users who try to achieve their physical goals in a gym setting. Doping within a gym setting is an issue of public health concern as most individuals use different substances without a doctor’s prescription or having proper knowledge of the associated risks of the substances. Also, some users buy nutritional supplements that contain steroids without their knowledge. The paper looks into the use of AI and machine learning as a solution to understanding the trends of gym users who are at risk of doping. The use of AI allows for early detection and behavioral pattern analysis, shifting focus from punitive enforcement practices to preventive care, a crucial element in promoting health training habits within the gym setting.