This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations, methods, methodologies, models, tools, and techniques for designing, developing, implementing and evaluating advanced DSSs in different fields, including finance, health, emergency management, industry and pollution control. Decision support systems employ artificial intelligence methods to heuristically address problems that are cannot be solved using formal techniques. In this context, technologies such as the Semantic Web, linked data, big data, and machine learning are being applied to provide integrated support for individuals and organizations to make more rational decisions. The book is organized into two parts. The first part covers decision support systems for industry, while the second part presents case studies related to clinical emergency management and pollution control.

This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.

Annotation The book presents state-of-the-art knowledge about decision-making support systems (DMSS). Its main goals are to provide a compendium of quality chapters on decision-making support systems that help diffuse scarce knowledge about effective methods and strategies for successfully designing, developing, implementing, and evaluating decision-making support systems, and to create an awareness among readers about the relevance of decision-making support systems in the current complex and dynamic management environment.

This book constitutes the proceedings of the 9th International Conference on Decision Support Systems Technologies, ICDSST 2023, held during May 30 – June 1, 2023. The EWG-DSS series of International Conference on Decision Support System Technology (ICDSST) is planned to consolidate the tradition of annual events organized by the EWG-DSS in offering a platform for European and international DSS communities, comprising the academic and industrial sectors, to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main theme of this year was “Decision Support Systems in An Uncertain World: The Contribution of Digital Twins”. The 21 papers presented in this volume were carefully reviewed and selected from 65 submissions. They were organized in topical sections as follows: DSS models, methods, and tools; DSS for business performance and stakeholders; DSS applications for sustainability in health, energy and transportation; and DSS users and successful adoption.

Appropriate for all courses in Decision Support Systems (DSS), computerized decision making tools, and management support systems. Todays networked computer systems enable executives to use information in radically new ways, to make dramatically more effective decisions -- and make those decisions more rapidly. Decision Support Systems and Intelligent Systems, Seventh Edition is a comprehensive, up-to-date guide to todays revolutionary management support system technologies, and how they can be used for better decision making. In this thoroughly revised edition, the authors go far beyond traditional "decision support systems," focusing far more coverage on Web-enabled tools, performance analysis, knowledge management, and other recent innovations. The authors introduce each significant new technology, show how it works, and offer practical guidance on integrating it into real-world organizations. Examples, products, services, and exercises are presented throughout, and the text has been revised for improved clarity and readability. New and enhanced coverage includes: state-of-the-art data mining, OLAP, expert system, and neural network software; revamped coverage of knowledge management; and a far greater emphasis on the use of Web technologies throughout. Also covered in detail: data warehousing, including access, analysis, visualization, modeling, and support. This edition also contains DSS In Action boxes presenting real business scenarios for the use of advanced management support technology. Decision Support Systems and Intelligent Systems, Seventh Edition is supported by a Web site containing additional readings, relevant links, and other supplements.