Artificial Intelligence in Healthcare: A Practical Guide

Abstract

This book, Artificial Intelligence in Healthcare: A Practical Guide, offers a comprehensive and practical exploration of the transformative role of Artificial Intelligence (AI) in the modern healthcare ecosystem. It traverses the evolution, integration, and application of AI technologies—from foundational concepts like machine learning, deep learning, natural language processing, and computer vision to their real-world deployment in diagnostics, imaging, personalized medicine, robotics, and healthcare administration. The book underscores how AI-driven systems enhance clinical decision-making, enable early and accurate diagnosis, streamline hospital operations, and support personalized patient care through data-driven insights. It also examines the digital transformation of healthcare, exploring how big data, cloud computing, and the Internet of Things (IoT) synergistically drive AI adoption. Each chapter reflects on the use of AI across medical domains such as radiology, pathology, genomics, surgery, and public health. The author critically addresses key challenges including algorithmic bias, data privacy, regulatory compliance, and ethical implications, while highlighting the future potential of technologies like explainable AI, federated learning, and quantum computing. Designed for practitioners, researchers, and students alike, the book serves as both an academic reference and a field guide, equipping readers with the knowledge and vision necessary to navigate and contribute to the rapidly evolving landscape of AI in healthcare.

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