Mohamed Abdel-Basset, Ripon Kumar Chakrabortty, Abduallah Gamal

Multi-Criteria Decision Making Theory and Applications in Sustainable Healthcare (eBook, PDF)

• Format: PDF

Produktbeschreibung

Multi-Criteria Decision Making Theory and Applications in Sustainable Healthcare, 1st Edition, is an excellent compilation of current and advanced Multi-Criteria Decision Making (MCDM) techniques and their applications to multiple recent and innovative healthcare analytics problems. The healthcare business has expanded rapidly in recent years, and one of the top priorities in the sector is now the efficacy and efficiency of the various healthcare delivery systems. The entire performance of hospitals must be improved if the healthcare business wants to see an improvement in both the satisfaction and safety of their patients. Finding the best medical facility among many of its competitors may be difficult since there are so many, and they are so highly diverse in terms of features and performance trade-offs.

This book has brought together the introductory discussions, fundamental concepts, challenges, and insights of multiple advanced healthcare management problems along with the application of MCDM to obtain the best option among multiple alternatives. A few important takeaways from this book are:

• Developing an efficient model for supplier performance evaluation and selection in healthcare industries with incomplete information
• A computational reliance approach for assessing healthcare service quality aspects and their measurement in an uncertain environment
• An efficient and provable approach for recommending suitable mobile healthcare products under uncertain environments
• Establishing a decision-making strategy to select healthcare waste treatment methods
• Assessing the usability of mHealth applications in practice related to type 2 diabetes

The successful outcome of this book will enable a decision-maker or practitioner to pick a suitable MCDM technique when making decisions to prioritize the selection criteria of any healthcare-related problems to ensure a sustainable practice.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 274
• Erscheinungstermin: 9. Mai 2023
• Englisch
• ISBN-13: 9781000867893
• Artikelnr.: 67764397

Autorenporträt

Mohamed Abdel- Basset (Senior Member, IEEE) received the B.Sc., M.Sc., and PhD degrees in operations research from the Faculty of Computers and Informatics, Zagazig University, Egypt. He is currently 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 conference.

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 PhD from the same University in 2017 while completing his MSc and BSc from Bangladesh University of Engineering and Technology in Industrial and 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.

Abduallah Gamal (Member, IEEE) is a senior researcher at Zagazig University, Faculty of Computers and Informatics, Department of Operations Research, Egypt. He obtained his bachelor's, master's, and PhD degrees in Information Systems in 2012, 2016, and 2021, respectively, from the Faculty of Computers and Informatics, Department of Operations Research, Zagazig University, Egypt. His area of interest includes computation intelligence, Optimization, Swarm Intelligence, Evolutionary Algorithms, and neutrosophic sets and logic. He is working on the application of multi-criteria decision-making. He is also a reviewer in different international journals and conferences. He has published more than 45 articles in international journals and conference proceedings.

Inhaltsangabe

Chapter 1. Developing an Efficient Model for Supplier Performance
Evaluation and Selection in Healthcare Industries with Incomplete
Information.
Chapter 2. A Consolidated Strategic for Analyzing and Ranking Smart
Healthcare Management System Portfolios in a Resource-Restricted
Environment.
Chapter 3. A Computational Reliance Approach for Assessing Healthcare
Service Quality Aspects and their Measurement in an Uncertain Environment.
Chapter 4. An Efficient Verified and Provable Approach for Recommending
Suitable Mobile Healthcare Products under Uncertainty Environment.
Chapter 5. Establishing a Decision-Making Strategy for a Causality Analysis
of Current Status and Potential Challenges and Selection of Healthcare
Waste Treatment Methods.
Chapter 6. Assessment the Usability and Understanding the Perception
Towards mHealth Applications in Practice Related to Type 2 Diabetes
Mellitus.
Chapter 7. Development of a Multi-Criteria Decision-Making Based Assessment
Model for Cloud Computing Adoption in the Medical and Healthcare Sector.
Chapter 8. An Optimized Neutrosophic Parameterized Multi-Criteria
Decision-Support System for a Medical Device Selection in the Healthcare
Industry.