A Review on Blockchain and Machine Learning in Healthcare

Abstract

Blockchain and machine learning are transformative technologies with the potential to significantly enhance the healthcare sector by addressing critical challenges such as operational efficiency, data security, and privacy. As a distributed ledger technology, blockchain enables secure and decentralized data sharing among healthcare systems, facilitating the safe exchange of sensitive patient information between hospitals, diagnostic labs, pharmaceutical companies, and patients. Blockchain applications in healthcare can improve patient privacy protection, electronic health record (EHR) management, and counterfeit drug tracking within pharmaceutical supply chains. When integrated with machine learning, blockchain fosters the development of advanced, patient-centric healthcare solutions. Its decentralized architecture ensures data integrity, prevents manipulation, and enhances security, while AI-powered analytics enable personalized medicine, real-time decision-making, and operational cost reduction. This synergy is expected to revolutionize healthcare by enabling applications such as secure medical data storage, pharmaceutical supply chain transparency, remote patient monitoring, and fraud prevention in clinical trials. By leveraging the complementary strengths of these technologies, healthcare systems worldwide can improve patient outcomes, enhance efficiency, and establish a more transparent and resilient infrastructure.