AI for Healthcare Fraud Detection: Leveraging Machine Learning to Combat Billing and Insurance Fraud
Abstract
Healthcare fraud, including fraudulent billing and insurance claims, is a significant challenge that affects healthcare systems globally. This paper investigates the use of AI and machine learning to detect and prevent healthcare fraud by analyzing patterns in billing data, insurance claims, and patient records. By applying anomaly detection algorithms and supervised learning models, AI can identify suspicious activities and flag potentially fraudulent claims in real time. The paper also explores the potential for AI to improve compliance monitoring, reduce financial losses, and enhance the integrity of healthcare systems, while addressing privacy concerns and ethical implications.
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