Applications Of Multi Criteria Decision Making Theories In Healthcare And Biomedical Engineering
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Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering
Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering contains several practical applications on how decision-making theory could be used in solving problems relating to the selection of best alternatives. The book focuses on assisting decision-makers (government, organizations, companies, general public, etc.) in making the best and most appropriate decision when confronted with multiple alternatives. The purpose of the analytical MCDM techniques is to support decision makers under uncertainty and conflicting criteria while making logical decisions. The knowledge of the alternatives of the real-life problems, properties of their parameters, and the priority given to the parameters have a great effect on consequences in decision-making. In this book, the application of MCDM has been provided for the real-life problems in health and biomedical engineering issues. - Provides a comprehensive analysis and application multi-criteria decision-making methods - Presents detail information about MCDM and their usage - Covers state-of-the-art MCDM methods and offers applications of MCDM for health and biomedical engineering purposes
Multiple-Criteria Decision-Making (MCDM) Techniques and Statistics in Marketing
Marketing has become increasingly popular, utilizing multi-criteria decision making (MCDM) methods and statistics to create robust frameworks for making informed and strategic decisions. Computational and modeling breakthroughs have resulted in a significant increase in the use of MCDM methods in marketing in the past decade, making it an ideal solution for many marketing problems. Statistics can now be used to conduct MCDM analyses on a variety of marketing problems, including new product introduction and pricing, using multiple data sources. Businesses can make more informed, strategic, and effective decisions by using MCDM methods and statistical analysis in marketing. By using these tools, marketers can improve market performance and competitive advantage by optimizing product development, pricing strategies, market segmentation, and campaign effectiveness. Multiple-Criteria Decision-Making (MCDM) Techniques and Statistics in Marketing explores the effects of MCDM techniques on marketing practices. It covers a wide range of statistics and research to examine MCDM in shaping modern consumer science. This book covers topics such as management science, product development, and consumer behavior, and is a useful resource for marketers, business owners, data scientists, academicians, and researchers.
Artificial Intelligence and Image Processing in Medical Imaging
Artificial Intelligence and Image Processing in Medical Imaging deals with the applications of processing medical images with a view of improving the quality of the data in order to facilitate better decision- making. The book covers the basics of medical imaging and the fundamentals of image processing. It explains spatial and frequency domain applications of image processing, introduces image compression techniques and their applications, and covers image segmentation techniques and their applications. The book includes object detection and classification applications and provides an overall background to statistical analysis in biomedical systems. The role of Machine Learning, including Neural Networks, Deep Learning, and the implications of the expansion of artificial intelligence is also covered. With contributions from prominent researchers worldwide, this book provides up-to-date and comprehensive coverage of AI applications in image processing where readers will find the latest information with clear examples and illustrations. - Provides the latest comprehensive coverage of the developments of AI techniques and the principles of medical imaging - Covers all aspects of medical imaging, from acquisition, the use of hardware and software, image analysis and implementation of AI in problem solving - Provides examples of medical imaging and how they're processed, including segmentation, classification, and detection