Decision support systems (DSS) are widely touted for their effectiveness in aiding decision making, particularly across a wide and diverse range of industries including healthcare, business, and engineering applications. The concepts, principles, and theories of enhanced decision making are essential points of research as well as the exact methods, tools, and technologies being implemented in these industries. From both a standpoint of DSS interfaces, namely the design and development of these technologies, along with the implementations, including experiences and utilization of these tools, one can get a better sense of how exactly DSS has changed the face of decision making and management in multi-industry applications. Furthermore, the evaluation of the impact of these technologies is essential in moving forward in the future. The Research Anthology on Decision Support Systems and Decision Management in Healthcare, Business, and Engineering explores how decision support systems have been developed and implemented across diverse industries through perspectives on the technology, the utilizations of these tools, and from a decision management standpoint. The chapters will cover not only the interfaces, implementations, and functionality of these tools, but also the overall impacts they have had on the specific industries mentioned. This book also evaluates the effectiveness along with benefits and challenges of using DSS as well as the outlook for the future. This book is ideal for decision makers, IT consultants and specialists, software developers, design professionals, academicians, policymakers, researchers, professionals, and students interested in how DSS is being used in different industries.

This textbook is a logical continuation of Dr. Tan's first book, Healt h Management Information Systems. For graduate level and upper level u ndergraduate courses, it explains the use of health decision support s ystems throughout the health care industry, citing examples from hospi tals, managed care organizations and long term care facilities. This b ook includes learning objectives, case studies and review questions. A n Instructor's guide is also available.

The development of artificial intelligence (AI) involves the creation of computer systems that can do activities that would ordinarily require human intelligence, such as visual perception, speech recognition, decision making, and language translation. Through increasingly complex programming approaches, it has been transforming and advancing the discipline of computer science. The Handbook of Research on AI Methods and Applications in Computer Engineering illuminates how today’s computer engineers and scientists can use AI in real-world applications. It focuses on a few current and emergent AI applications, allowing a more in-depth discussion of each topic. Covering topics such as biomedical research applications, navigation systems, and search engines, this premier reference source is an excellent resource for computer scientists, computer engineers, IT managers, students and educators of higher education, librarians, researchers, and academicians.

Machine learning (ML) and intelligent systems are now comprehensively applied for the solving of practical problems. Emerging techniques such as big data analysis, deep neural networks, AI, and IoT have been adopted and integrated into the development and application of machine learning and intelligent systems, and their wide application in industry, medicine, engineering, education and other mainstream domains have made them a part of everyday life. This book presents the proceedings of MLIS 2023, the 5th International Conference on Machine Learning and Intelligent Systems, held as a hybrid event from 17-20 November 2023 in Macau, China. This annual conference aims to provide a platform for a knowledge exchange of the most recent scientific and technological advances in the field of ML and intelligent systems, and to strengthen links within the scientific community in related research areas. A total of 80 submissions were received for the conference, of which 20 papers were selected for presentation and publication in these proceedings following a rigorous peer-review process. Papers were assessed on originality, scientific/practical significance, compelling logical reasoning and language, and the selected papers cover a wide range of topics, and provide innovative and original ideas or results of general significance in the field of ML and intelligent systems. Providing a current overview of developments in the fields of machine learning and intelligent systems, the book will be of interest to all those working in this field.