AI-Driven Medical Fund Verification System to Detect and Prevent Fraudulent Treatment Requests

DOI

https://www.doi.org/10.59256/ijire.20260702022

Published In

Volume 7, Issue 2 (2026)

Published Online

March-April 2026

Pages

172-176

Article Type

Original Article

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Medical crowdfunding has become a crucial support system for patients requiring urgent financial assistance. However, the rise of fraudulent treatment requests using manipulated medical bills and fake documents has significantly reduced donor trust. Traditional verification methods rely heavily on manual review, which is time-consuming, inefficient, and often incapable of detecting sophisticated fraud.This paper proposes an AI-driven medical fund verification system that automates the authentication process using advanced deep learning and text recognition techniques. The system employs YOLOv8 for detecting text regions in medical bills and PaddleOCR for extracting relevant patient and hospital information. The extracted data is then validated against trusted hospital records using a Fuzzy Matching Algorithm to identify inconsistencies and detect fraudulent claims.The proposed solution enhances transparency, improves efficiency, and strengthens donor confidence by ensuring that only genuine medical fund requests are approved.