Big Data Concept

  Introduction Quantum computing, a revolutionary paradigm leveraging the principles of quantum mechanics, is poised to transform various fields, including healthcare. Unlike classical computers that process information using bits (0s and 1s), quantum computers use quantum bits or qubits, which can exist in superpositions, enabling exponentially faster computations for specific problems. In healthcare, quantum computing holds immense potential for applications in genomics, medical imaging, and patient data analysis. These areas require processing vast datasets, optimizing complex algorithms, and solving problems intractable for classical computers. This chapter explores how quantum computing can enhance these domains, addressing current challenges, potential applications, and future implications. Quantum Computing in Genomics Genomics, the study of an organism's complete set of DNA, involves analyzing vast amounts of genetic data to understand biological processes, disease mecha...

 Healthcare has always been a data-rich field, but the rapid growth of electronic health records (EHRs), diagnostic imaging, wearable devices, and genomics has created an overwhelming flood of information. Traditional systems often fail to process, analyze, and interpret such massive datasets in real time. This is where Agentic AI —autonomous, goal-driven, and adaptive AI systems—emerges as a transformative force in healthcare. By harnessing the power of big data, Agentic AI is reshaping how medical professionals deliver care, improving efficiency, accuracy, and most importantly, patient outcomes. 1. The Convergence of Big Data and Agentic AI in Healthcare Big data in healthcare includes structured information (EHRs, lab results), semi-structured data (clinical notes), and unstructured data (medical images, genomics, wearable sensor streams). The scale is massive, but traditional analytics often struggle with speed, accuracy, and contextual relevance. Agentic AI introduces ...

  Introduction In the rapidly evolving landscape of healthcare, big data has emerged as a transformative force, enabling unprecedented insights into patient care, disease management, and operational efficiency. Defined by its volume, variety, velocity, and veracity, big data encompasses vast datasets from electronic health records (EHRs), wearables, genomic sequencing, and more, generating over 2,314 exabytes daily by 2025. This chapter explores how big data is revolutionizing patient care, from predictive analytics to personalized medicine, while addressing benefits, challenges, and future trends. As of 2025, integrations of artificial intelligence (AI) and big data analytics are not only improving outcomes but also bridging gaps in access, with AI expected to accelerate markets like traditional, complementary, and integrative medicine (TCIM) to nearly $600 billion. Sources of Big Data in Healthcare Big data in healthcare draws from diverse sources, creating a rich ecosystem...