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Advances in Computational Intelligence for Health Informatics and Computer–Aided Diagnosis Methods, Applications, and Tools

   Author: creativelivenew1   |   10 March 2025   |   Comments icon: 0

Advances in Computational Intelligence for Health Informatics and Computer–Aided Diagnosis Methods, Applications, and Tools
Free Download Advances in Computational Intelligence for Health Informatics and Computer-Aided Diagnosis: Methods, Applications, and Tools
by Malini, A., Bhatia Khan, Surbhi, Kayalvizhi, S., Saraee, Mohammed

English | 2025 | ISBN: 1032776579 | 297 pages | True PDF EPUB | 56.43 MB


This book provides a comprehensive overview of the intersection of computational intelligence, health informatics, and computer-aided diagnosis (CAD). The book explores and highlights the latest advancements, methodologies, applications, and tools in these fields.
Advances in Computational Intelligence for Health Informatics and Computer-Aided Diagnosis: Methods, Applications, and Tools covers a broad spectrum of computational intelligence approaches, from basic concepts to advanced methodologies. The focus on health informatics reflects the book's commitment to researching data integration, privacy issues, and interoperability issues that are crucial in today's healthcare landscape. The book's core is its in-depth examination of CAD systems, which encompasses numerous healthcare sectors and underlines the technological complexity involved in building accurate and efficient diagnostic tools. Some of the other key areas covered include: medical imaging analysis, disease identification and diagnosis, and drug research and development. It also provides case studies that demonstrate how computational intelligence methods are applied in real-world healthcare scenarios, giving readers a practical understanding of the subject matter. The authors then discuss future trends and directions in computational intelligence for health informatics.
The book is designed to serve as a guide to for academics, professionals, and students who are curious about the challenges of integrating contemporary computational approaches into medical diagnostics and decision support.



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