AI-Powered Diagnostics: Advances in Biomedical Imaging and Predictive Analytics: Emerging Trends in Biomedical Technologies and Health informatics
Editat de Suneeta Satpathy, Sachi Nandan Mohanty, Subhendu Kumar Pani, Zahid Akhtar, Weiwei Jiangen Limba Engleză Hardback – 30 sep 2027
Covering foundations of AI in biomedical diagnostics, AI in biomedical and predictive imaging, and emerging applications and future directions, this book:
• Explores how AI algorithms are being integrated into medical imaging systems across modalities like MRI, CT, and pathology slides.
• Covers applications of machine learning and deep learning fundamentals for healthcare applications.
• Explains data acquisition and preprocessing for AI-powered diagnostic systems.
• Presents real-world case studies illustrating clinical implementation of AI-powered diagnostic tools.
• Discusses predictive analytics models for early disease detection, treatment planning, and outcome forecasting.
• Reviews ethical and regulatory frameworks, data privacy issues, and model explainability in clinical AI.
This book is primarily written for biomedical engineers designing diagnostic systems, clinicians seeking to understand AI integration in radiology, researchers advancing predictive health analytics, and diverse audiences in academic, clinical, and industrial settings.
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Specificații
ISBN-13: 9781041219835
ISBN-10: 1041219830
Pagini: 464
Ilustrații: 286
Dimensiuni: 156 x 234 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Emerging Trends in Biomedical Technologies and Health informatics
ISBN-10: 1041219830
Pagini: 464
Ilustrații: 286
Dimensiuni: 156 x 234 mm
Ediția:1
Editura: CRC Press
Colecția CRC Press
Seria Emerging Trends in Biomedical Technologies and Health informatics
Public țintă
Postgraduate, Undergraduate Advanced, and Undergraduate CoreCuprins
1. Introduction to AI in Diagnostic Medicine: Challenges and Opportunities. 2. Explainable Artificial Intelligence and Trustworthy Systems for Clinical Integration. 3. Wellness Centric Intelligent Healthcare Systems of Drug Discovery. 4. DETECTION AND PREDICTION OF BRAIN TUMOR USING DEEP LEARNING SENT VIA MAIL WITH EFFICIENT SMTP. 5. Enhanced MRI Brain Tumor Detection Using Adaptive Bayesian Dual-Channel Networks and Nature-Inspired Optimization. 6. Lightweight Deep Learning Models for Medical Image Classification: A Comparative and Efficient Approach. 7. Automated Liver Cancer Detection Using a Nested Graph Cell Neural Network Optimized with Success-Based Algorithm for Enhanced Accuracy and Robust Classification of CT Images. 8. Deep Learning-Based Eye Disease Detection Using Retinal Fundus Imaging: Methods, Architecture, and Clinical Applications. 9. Harnessing CNN for Handwriting Recognition in Healthcare. 10. An Intelligent Predictive Analytics Framework Using Optimized Deep Neural Networks for Skin Lesions Image Analysis. 11. Predictive Analytics for Cardiac Risk Assessment Using Multivariate Health Data. 12. Heart-Attack prediction evaluation using a fuzzy rule-based system. 13. Pancreatic Cancer Prediction Using LSTM. 14. A Hybrid GAN–Marine Predators Algorithm Framework for Enhanced EEG-Based Alzheimer’s Disease Classification. 15. Multimodal Alzheimer’s Detection System Using Machine Learning Techniques. 16. BioSync360: An AI and IoT-Based Multi-Sensor Framework for Real-Time Healthcare Monitoring and Early Disease Prediction. 17. Greenvoy: Implementation of a Smart Ambulance Routing and Patient Health Monitoring System Using Green AI and IoT. 18. Multimodal Fatigue Detection Across Populations: A Meta-Analytic Review of Physiological Sensors, AI Models, and Subjective Scales. 19. AI-Enabled IoT Sensor Networks for Resilient 6G Healthcare Communication Systems. 20. Real-Time Vision and Navigation Aid for the Visually Impaired Using YOLO and GPS Integration. 21. Neuro-Symbolic Graph-Transformer Architectures for Mechanism-Aware Disease Analysis. 22. Genomic Data Analysis Platform using XGBoost and FT Transformer for Gene-Drug Responses. 23. Machine Learning, Deep Learning and Transformer Techniques for Lung Cancer Detection. 24. AI-Enabled Biomedical Imaging and Nanomaterial Innovations for Sustainable Industry 4.0 Systems. 25. A Progressive Feedback Cosine Convolutional Neural Network Framework with Nadam Optimization for Robust IoT Healthcare Access Control. 26. Integration and Closed-Loop Simulation of Whole-Brain Spiking Neural Networks with a Rodent Musculoskeletal Model for Studying Contextual Decision-Making and Behavioral Adaptation. 27. Virtual Brain Twin for Personalized Treatment of Psychiatric Disorders. 28. SmartGuard: An Intelligent Physical and Emotional Safety System for the Elderly. 29. AI-Powered Indoor Air-Quality Monitoring and Prediction System Using IoT and Machine Learning. 30. Federated Deep Learning frameworks for privacy-preserving collaborative diagnosis using multimodal medical imaging and electronic health records.
Notă biografică
Suneeta Satpathy is affiliated with the Center For Cyber Security at SoA Deemed to be University in Bhubaneswar, Odisha, India. Her research focuses on cybersecurity and related technologies.
Sachi Nandan Mohanty serves as Professor in the School of Computer Science and Engineering at VIT-AP University, Amaravati, Andhra Pradesh, India. His expertise spans computer science with emphasis on engineering applications.
Subhendu Kumar Pani is Professor in the School of Computer Science and Engineering at Krupajal Engineering College, affiliated with BPUT, Odisha, India. His research interests include computer science and engineering disciplines.
Zahid Akhtar is affiliated with the Department of Network and Computer Security at State University of New York, Polytechnic Institute, USA. His work focuses on network security and computer systems protection.
Weiwei Jiang is based in the School of Information and Communication Engineering at Beijing University of Posts and Telecommunications in Beijing, China. His research encompasses information systems and communication technologies. Professor Jiang specializes in advancing information and communication engineering solutions.
Sachi Nandan Mohanty serves as Professor in the School of Computer Science and Engineering at VIT-AP University, Amaravati, Andhra Pradesh, India. His expertise spans computer science with emphasis on engineering applications.
Subhendu Kumar Pani is Professor in the School of Computer Science and Engineering at Krupajal Engineering College, affiliated with BPUT, Odisha, India. His research interests include computer science and engineering disciplines.
Zahid Akhtar is affiliated with the Department of Network and Computer Security at State University of New York, Polytechnic Institute, USA. His work focuses on network security and computer systems protection.
Weiwei Jiang is based in the School of Information and Communication Engineering at Beijing University of Posts and Telecommunications in Beijing, China. His research encompasses information systems and communication technologies. Professor Jiang specializes in advancing information and communication engineering solutions.
Descriere
AI-Powered Diagnostics: Advances in Biomedical Imaging and Predictive Analytics explores the challenges and opportunities associated with AI integration in biomedical imaging and predictive analytics for healthcare diagnostics.