• Siddhesh Gadewar
• Anushka Sable
• Srujan Bele
• Vedika Gawner
• Bhavesh Thakare

Anti-doping agencies must analyze large volumes of athlete testing data to detect suspicious patterns and protect the integrity of sports. Traditional methods often rely on manual analysis, which can be slow and inefficient when handling complex biological data. This review paper explores the role of Artificial Intelligence in improving anti-doping monitoring and investigation. It discusses the concept of NADARAI, an AI-powered platform designed to analyze athlete biological parameters and identify abnormal trends using machine learning and rule-based analysis. By combining anomaly detection, risk scoring, and visual dashboards, the system can help authorities quickly identify high-risk cases and support better decision-making. The study highlights how AI-driven technologies can enhance efficiency, transparency, and accuracy in modern anti-doping systems.

Artificial Intelligence, Sports Data Analytics, Anti-Doping Systems, Athlete Biological Passport, Machine Learning, Anomaly Detection,

"NADARAI - Redefining Anti-Doping Through Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 3, page no.d382-d386, March-2026, Available :http://www.jetir.org/papers/JETIR2603344.pdf

"NADARAI - Redefining Anti-Doping Through Artificial Intelligence", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 3, page no. ppd382-d386, March-2026, Available at : http://www.jetir.org/papers/JETIR2603344.pdf