Integrating NLP and Big Data for Cognitive Decision Intelligence in Business, Healthcare, and Governance

The rapid growth of data-driven technologies has significantly transformed the way decisions are made across critical sectors such as business, healthcare, and governance. Advances in Natural Language Processing (NLP) and Big Data analytics have enabled intelligent systems to move beyond descriptive analysis toward cognitive decision intelligence, where data is interpreted, contextualized, and transformed into actionable insights. This book, Integrating NLP and Big Data for Cognitive Decision Intelligence in Business, Healthcare, and Governance, is conceived in response to this technological shift and the growing need for interdisciplinary research in this domain.

This edited volume presents a collection of original research papers, each included as an independent chapter, contributed by academicians, researchers, and practitioners. The chapters collectively explore theoretical foundations, methodological frameworks, and real-world applications of NLP, machine learning, deep learning, and big data analytics in decision intelligence systems. Special emphasis is placed on healthcare analytics, disease prediction, clinical text mining, intelligent surveillance, data privacy, and governance-oriented AI solutions.

The contributions included in this book address both foundational and advanced topics, ranging from data management and predictive modeling to explainable and ethical AI systems. While each chapter can be read independently, together they provide a coherent and comprehensive overview of contemporary research trends and challenges in cognitive decision intelligence across multiple domains.

This book is intended for research scholars, postgraduate students, academicians, and industry professionals who are engaged in artificial intelligence, data science, healthcare analytics, and intelligent decision support systems. It is hoped that this volume will serve as a valuable reference for ongoing research, foster academic collaboration, and stimulate future innovations in the integration of NLP and big data technologies for intelligent decision-making.

The editors sincerely acknowledge the efforts of all contributing authors and reviewers whose scholarly work has made this compilation possible. It is our hope that this book will contribute meaningfully to the advancement of knowledge and practical applications in the evolving field of cognitive decision intelligence.