Transforming Healthcare: The Integration of Artificial Intelligence and Big Data

Abstract

The integration of Artificial Intelligence (AI) and Big Data technologies is reshaping the landscape of modern healthcare. These technologies enable unprecedented capabilities in disease diagnosis, treatment planning, drug discovery, and health system optimization. AI algorithms, powered by machine learning and deep learning, are increasingly used to analyze complex medical data, uncover hidden patterns, and support clinical decisions with high precision. Meanwhile, big data platforms process massive, heterogeneous health data from electronic health records (EHRs), genomic sequencing, wearable devices, and public health databases to generate actionable insights. This paper explores the foundational technologies, key applications, and significant impacts of AI and big data in healthcare. It also addresses ethical, legal, and technical challenges, including data privacy, algorithmic bias, and regulatory compliance. Finally, the paper highlights future directions such as explainable AI, federated learning, and multi-modal data integration, emphasizing the need for interdisciplinary collaboration to realize the full potential of these technologies in advancing global health outcomes.