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      • Nyhet

      Intelligent Semantic Analysis for Healthcare

      AvSonali Vyas,Samiya Khan

      Häftad, Engelska, 2026

      1 824 kr

      Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

      Beskrivning

      Intelligent Semantic Analysis for Healthcare explores the latest trends, developments, and future directions of intelligent semantic analysis techniques on retrieving and managing meaningful medical information for healthcare information systems. The book explores different computational methods, ideas, strategies, and techniques to analyze relevant healthcare information in an innovative and efficient way, thus bridging the gap between gathering and comprehending data with healthcare and biological applications. It offers a comprehensive view of intelligent semantic analysis in healthcare, bridging the gap between data collection and healthcare applications, and providing innovative computational methods for data analysis.

      Sections focus on intelligent semantic analysis rather than broader topics of big data and healthcare analytics. Additionally, the book is geared towards practical approaches and innovative techniques for state-of-the-art and current challenges in healthcare data management.

      • Explores the operation of future healthcare data systems, enhancing clinical resources to ensure optimal patient outcomes
      • Highlights trends, challenges, opportunities, and future areas in healthcare informatics, focusing on accessing extensive datasets containing potentially lifesaving information
      • Presents case studies that demonstrate the intelligent analysis of healthcare information through the combination of real-time data, predictions, and advanced computer programs

      Produktinformation

      • Utgivningsdatum:2026-08-28
      • Mått:191 x 235 x undefined mm
      • Vikt:450 g
      • Format:Häftad
      • Språk:Engelska
      • Antal sidor:470
      • Förlag:Elsevier Science
      • ISBN:9780443335129

      Utforska kategorier

      • Artificiell intelligens inom Data och IT
      • Hälsoinformatik inom Medicin

      Mer om författaren

      Sonali Vyas is an academician and researcher for more than 12 years. She is a Senior Member-IEEE and Lifetime member of CSI. She is an active researcher, and her prime areas of research are healthcare informatics, data analytics and mining. She has authored around 40 research papers, articles and chapters in SCI/WOS/Scopus-indexed journals/conference proceedings and books. She has also authored and edited many books in the areas of machine learning, telemedicine, artificial intelligence, healthcare, blockchain, etc. She is also a member of the Editorial Board and Reviewer Board in many referred National and International journals. She has also been a member of the Organizing Committee, National Advisory Board, and Technical Program Committee at many International and National conferences. She has also Chaired Sessions at various reputed International and National Conferences. Dr. Samiya Khan is Assistant Professor of Computer Science at the University of Southampton Delhi and a Fellow of the Higher Education Academy (HEA). Her research focuses on data science, ethical artificial intelligence, and the application of AI in Internet of Things (IoT) environments. Her work spans digital health, green computing, responsible AI, and interdisciplinary approaches to emerging technologies. In addition to her research and teaching activities, she serves as a Women in Data Science (WiDS) Ambassador, supporting initiatives that promote diversity and inclusion in technology. Priyadarsan Patra is the pro-vice-chancellor of DIT University, India. He served as chief architect and principal scientist of R&D at Intel Corp (USA), as dean of Computer Sciences at UPES University and dean of Research at Xavier University. Author of 75+ scholarly publications, four books, 13 international patents, Senior Member of IEEE and ACM, and an IE Fellow. His research interests include intelligent systems architecture, and he founded IEEE System Validation and Debug Technology Committee. Gianluigi Ferrari is an associate professor of Telecommunications at the University of Parma, Italy, where he coordinates the Internet of Things (IoT) Lab at the Department of Engineering and Architecture. He has written over 400 scientific papers/book chapters/books/patents and is an IEEE Senior Member. His research interests include IoT, networking, and smart systems. Assoc. Prof. Dr. Korhan Cengiz is a senior researcher at the University of Hradec Králové, Czech Republic, and Associate Professor at Istinye University, Turkey. He holds a PhD in Electronics Engineering from Kadir Has University and has held academic roles in Turkey, the UAE, and Jordan. Dr. Cengiz has authored over 40 SCI/SCI-E articles, 10+ book chapters, 5 international patents, and edited more than 20 books. His research focuses on wireless sensor networks, IoT, signal processing, and 5G. He serves as Associate Editor for IEEE Transactions on Intelligent Transportation Systems, IEEE Potentials, and IET journals, and is a frequent keynote speaker at IEEE and Springer conferences. A Senior Member of IEEE and ACM, he has received multiple awards, including best paper and presentation honors at ICAT conferences.

      Innehållsförteckning

      • Part I: Foundational Frameworks of Intelligent Healthcare1. Advanced Data Analysis Techniques for Healthcare Informatics2. From Efficiency to Sustainability: The Evolution of Smart Healthcare Systems3. Architectural Analysis of Cyber Physical Systems for Healthcare – A ReviewPart II: The Physical Layer: IoT, Wearables, and Cyber-Physical Systems4. Transforming Healthcare with Intelligent Data Analysis: Harnessing Wearable Technology, Generative AI, and Cloud Computing5. Current Trends in IoT-Enabled Healthcare for Wellness Management6. Semantic Interoperability for the Internet of Medical Things (IoMT): From Wearables to Standards7. Medical Cyber Physical Systems (MCPS) for patient monitoring and treatmentPart III: The Semantic Heart: LLMs, Knowledge Graphs, and Interoperability8. Enhanced semantic model in Healthcare9. Large Language Models in Healthcare Semantics10. Hybrid Semantic Statistical Architectures for Explainable and Trustworthy Clinical Decision Support Systems11. Semantic Clinical Decision Support Systems: Challenges and Future ScopePart IV: Clinical Intelligence: Domain-Specific Applications12. Multimodal Semantic Integration in Radiology: From Pixels to Clinical Knowledge Graphs13. A Framework for Brain Tumor (Glioma) Analysis using SVM and Graph Convolutional Networks14. Sentinel Eye: Hybrid AI for Non-Invasive Anemia Detection Using Eye Scans, Symptoms, and HistoryPart V: Trust and Resilience: Security, Privacy, and Explainability15. Semantic Computing in Healthcare: Bridging The Gap Between Innovation and Privacy Security Measures16. Securing Cyber Physical Systems in Healthcare using Blockchain17. Exploring Security and Privacy Challenges in Intelligent Semantic HealthcarePart VI: Sustainability, Policy, and the Future Landscape18. Sustainable Futures: Advancing Healthcare Responsibly19. Embedding Sustainability into Work-Life Balance Practices with Special Reference to Healthcare Sector20. The Role of the National Health Digitization Agency (NHDA) in Digitizing the Algerian Health Sector: Between Reality and Prospects Contributors21. Smart Healthcare Systems: In the Era of Metaverse, Artificial Intelligence, and Data Science22. Challenges and Future Scope of Intelligent Semantic Healthcare
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