Abstract

Medical crowdfunding has increasingly become a crucial method for individuals to gather funds during medical crises. Nevertheless, conventional crowdfunding platforms face challenges such as fraudulent initiatives, unclear fund distribution, and ineffective targeting. This study introduces a comprehensive framework that utilizes blockchain technology and Machine Learning (ML) to improve transparency, security, and efficiency in medical crowdfunding. Blockchain technology is used to establish an unchangeable and decentralized record of transactions while facilitating automated fund management through smart contracts. At the same time, ML algorithms evaluate campaign data to identify fraud, verify legitimacy, and forecast campaign success. Our proposed system is assessed against current solutions and shows notable enhancements in reliability and performance. The paper includes comparative analysis, architectural diagrams, and performance assessment utilizing both real and synthetic datasets, effectively advocating for the implementation of intelligent, decentralized medical crowdfunding systems.

Keywords: Medical crowdfunding, Healthcare fundraising, Blockchain, Machine learning