Machine learning-based detection of medical service anomalies: Kazakhstan’s health insurance data - Maksut Kulzhanov; Alexander Wagner; Abylkair Skakov; Iliyas Mukhamejan; Saya Zhorabek; Ainur B. Qumar (Central Asian Journal of Medical Hypotheses and Ethics)
Background. With the exponential growth of medical data and limited analytical resources, healthcare systems are increasingly adopting Artificial Intelligence (AI) and Machine Learning (ML) technologies to enhance their decision-making processes. This research aims to apply advanced ML algorithms to analyze data from the Republic of Kazakhstan’s Obligatory Health Insurance Fund (OHIF) and automatically detect anomalies in the structure of delivered medical services.