ML And Blockchain in Healthcare

Abstract

: The integration of Machine Learning (ML) and Blockchain technology in healthcare has the potential to revolutionize the industry by enhancing data security, privacy, and decision-making. This paper explores the synergy between ML and blockchain in creating a more robust, efficient, and decentralized healthcare system. Machine Learning models enable predictive analytics, personalized treatment plans, and anomaly detection, while blockchain ensures secure, immutable, and transparent data sharing across stakeholders. Together, these technologies address critical challenges such as data interoperability, patient privacy, and healthcare fraud. We present a comprehensive analysis of current applications, including patient data management, drug supply chain tracking, and predictive healthcare models. Furthermore, the paper discusses key challenges, such as scalability, data standardization, and computational costs, along with potential future directions for research in this interdisciplinary domain. Our findings suggest that a combined approach of ML and blockchain can significantly enhance the quality of healthcare services by fostering trust, reducing inefficiencies, and empowering patients and healthcare providers with better data-driven insights.