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AI and Data Engineering for Healthcare: Real-World Applications and Case Studies

Edited by Anjan Bandyopadhyay, Edited by Tanvir Habib Sardar, Edited by Saurav Mallik, Edited by Ruhul Amin Hazarika, Edited by Mahendra Kumar Gourisaria

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This book examines the transformative role of artificial intelligence (AI) and data engineering in revolutionizing the healthcare landscape. It presents cutting-edge developments ranging from predictive algorithms for disease diagnosis to large-scale data systems that enhance patient outcomes. By emphasizing the synergy between AI and data engineering, the book showcases practical applications in medical imaging, clinical diagnostics, and personalized treatment strategies. It also thoughtfully examines ethical considerations, data privacy, and healthcare equity, particularly in underserved and rural populations. Key Features: Explores state-of-the-art technologies in healthcare, including image segmentation, feature extraction, feature selection, and classification. Provides real-world case studies, practical examples, and hands-on exercises for effective implementation of AI-driven solutions. Bridges disciplines across computer science, data engineering, and biomedical sciences to foster cross-domain collaboration. Highlights innovative research methodologies and their applications in AI-powered healthcare systems. Discusses the role of AI in improving healthcare access, delivery, and outcomes across diverse populations. This book is ideal for professionals, researchers, and policymakers seeking to understand and shape the future of healthcare through the lens of AI and data-driven innovation.

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