Application of Advanced Optimization Techniques for Healthcare Analytics

1. Auflage 2024
ISBN: 978-1-032-35158-2
Verlag: Taylor & Francis Ltd (Sales)

Buch, Englisch, 244 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 349 g

Application of Advanced Optimization Techniques for Healthcare Analytics, 1st Edition, is an excellent compilation of current and advanced optimization techniques which can readily be applied to solve different hospital management problems. The healthcare system is currently a topic of significant investigation to make life easier for those who are disabled, old, or sick, as well as for young children. The emphasis of the healthcare system has evolved throughout time due to several emerging beneficial technologies, such as personal digital assistants (PDAs), data mining, the internet of things, metaheuristics, fog computing, and cloud computing.

Metaheuristics are strong technology for tackling several optimization problems in various fields, especially healthcare systems. The primary advantage of metaheuristic algorithms is their ability to find a better solution to a healthcare problem and their ability to consume as little time as possible. In addition, metaheuristics are more flexible compared to several other optimization techniques. These algorithms are not related to a specific optimization problem but could be applied to any optimization problem by making some small adaptations to become suitable to tackle it.

The successful outcome of this book will enable a decision-maker or practitioner to pick a suitable optimization approach when making decisions to schedule patients under crowding environments with minimized human errors.

Zielgruppe

Academic

Autoren/Hrsg.

Abdel-Basset, Mohamed

Chakrabortty, Ripon K

Mohamed, Reda

Fachgebiete

• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Technische Wissenschaften Energietechnik | Elektrotechnik Elektrotechnik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik

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 Autor(innen)

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.