Using ML to identify Fraudulent Activities in Healthcare Industry
Sonam Juneja, Chanchal Kumar, Bhoopesh Singh Bhati, Reema Goyal, Rajat Dubey, Souvik Maiti · 2025
This research belongs to comprehensive analysis of fraudulent activities going on in health care industry using machine learning. The study made a systematic approach in methodologies from various medical field. The systematic reviews and Meta analysis synthesizes the fraudulent in the health sector. This paper introduce few models like Support Vector Machine, K-Nearest Neighbors, Random Forest, Logistic Regression. There are few parameters in the healthcare which impacts majority of the patient in the nationwide. Medicare fraud is a very serious issue where only old data sets and prediction are made which is also not 100% accurate. It only deals in prediction the more raw data the higher accuracy. Fraudulent activities in healthcare are increasing day by day which is a very big burden on the society. Patient multiple visits or routine checkup can also improve the prediction as they are also very well aware of the same. The research is all about detecting and preventing the fraud activities done in health care sector.