Mehr lesen
This book demonstrates how optimization techniques can solve hospital analytics problems. It covers advanced heuristic, meta-heuristic, DL/ML, multi-criteria decision making (MCDM), and prescriptive models, but also encompasses different supply chain, logistics, planning, scheduling, and medical imaging issues related to hospital analytics.
Inhaltsverzeichnis
1. Advanced Optimization Techniques (Introduction) 2. Metaheuristic Algorithms for Healthcare: Open Issues and Challenges 3. Metaheuristic-Based Augmented Multilayer Perceptrons for Cancer and Heart Disease Predictions 4. The Role of Metaheuristics in Multilevel Thresholding Image Segmentation 5. Role of Advanced Metaheuristics for DNA Fragment Assembly Problem. 6. Contribution of Metaheuristic Approaches for Feature Selection Techniques 7. Advanced Metaheuristics for Task Scheduling in Healthcare IoT 8. Metaheuristics for Augmenting Machine Learning Models to Process Healthcare Data 9. Deep Learning Models to Process Healthcare Data: Introduction 10. Metaheuristics to Augment DL Models Applied for Healthcare System 11. Intrusion Detection System for Healthcare System Using Deep Learning and Metaheuristics.
Über den Autor / die Autorin
MOHAMED ABDEL-BASSET (Senior Member, IEEE) received the BSc, MSc, and Ph.D degrees in operations research from the Faculty of Computers and Informatics, Zagazig University, Egypt. He is currently an Associate Professor with the Faculty of Computers and Informatics, Zagazig University. He has published more than 200 articles in international journals and conference proceedings. He is working on the application of multi-objective and robust metaheuristic optimization techniques. His current research interests include optimization, operations research, data mining, computational intelligence, applied statistics, decision support systems, robust optimization, engineering optimization, multi-objective optimization, swarm intelligence, evolutionary algorithms, and artificial neural networks. He is an editor and a reviewer of different international journals and conferences.
RIPON K. CHAKRABORTTY (Senior Member, IEEE) is the Program Coordinator for Master of Decision Analytics and Master of Engineering Science Programs, and the team leader of ‘Decision Support & Analytics Research Group’ at the School of Engineering & Information Technology, UNW Canberra, Australia. He obtained his Ph.D from the same University in 2017 while completing his MSc and BSc from Bangladesh University of Engineering & Technology in Industrial & Production Engineering in 2013 and 2009, respectively. He has written four book chapters and over 170 technical journal and conference papers. His research interest covers a wide range of topics in operations research, project management, supply chain management, artificial intelligence, and information systems management. Many organizations have funded his research program, such as the Department of Defence, Commonwealth Government, Australia. He is an associate editor and a reviewer of different international journals and conferences.
REDA MOHAMED received his BSc degree from the Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, Egypt. He is working on the application of multi-objective and robust metaheuristic optimization techniques in computational intelligence. His research interests include robust optimization, multi-objective optimization, swarm intelligence, evolutionary algorithms, and artificial neural networks.
Zusammenfassung
This book demonstrates how optimization techniques can solve hospital analytics problems. It covers advanced heuristic, meta-heuristic, DL/ML, multi-criteria decision making (MCDM), and prescriptive models, but also encompasses different supply chain, logistics, planning, scheduling, and medical imaging issues related to hospital analytics.
