Decision Support Systems (DSSs) are Software and Information Systems which make use of various data and business models, employ advanced data analytics procedures, and access extensive databases and data warehouses to facilitate with a decision process or with organizational issues. DSSs have proven to be particularly useful at the strategic level, while they usually require only limited computer-proficiency skills from their users. Although DSSs have been under development and use for several decades, recent advances in both Software Engineering technologies and Artificial Intelligence (AI) methodologies have heralded new avenues for research and development in this field.

This book exposes its readers to some of the most significant Advances in Artificial Intelligence-Empowered Decision Support Systems. It consists of an editorial note and an additional sixteen (16) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. The chapters are organized into five parts, namely (i) AI-Empowered DSS in Medical Diagnosis and Biology, (ii) AI-Empowered DSS in Healthcare and Health Insurance, (iii) AI-Empowered DSS in Urban Matters, (iv) Various Applications of AI-Empowered DSS, and (v) Novel AI-Empowered Methodologies in Decision Making.

Targeted toward academics, researchers, practitioners, and students in Computer Science, Artificial Intelligence, and Management, this book is also accessible to individuals from other disciplines interested in the cutting-edge developments of AI-empowered DSS technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into the application areas of interest to them.

Exposes its readers to some of most significant Advances in Artificial Intelligence-Empowered Decision Support Systems Consists of an editorial note and an additional fifteen chapters Guides the readers to probe deeper into the application areas of interest to them

Autorentext

GEORGE A. TSIHRINTZIS received the Diploma of Electrical Engineering from the National Technical University of Athens, Greece (with honors) and the M.Sc. and Ph.D. degrees in Electrical and Computer Engineering from Northeastern University, Boston, Massachusetts, USA. He is currently a Professor in The University of Piraeus, Greece and, during 2016-2020, he served as Head of its Department of Informatics. From 2008 to 2022, he served as the Director of the Graduate Program of Study in "Advanced Computing and Informatics Systems" of the Department. During the period 2016-2020, he was a Member of the first Administration Council of the University of Piraeus. Currently, he is serving again as a Member of the Administration Council of the University of Piraeus for a four-year term (2022-2026). His current research interests include Artificial and Computational Intelligence, Machine Learning, Pattern Recognition, Decision Theory, and Statistical Signal Processing and their applications in Internet-of-Things Technologies, Multimedia Interactive Services, User Modeling, Knowledge-based Software Systems, Human-Computer Interaction and Information Retrieval. He has authored or co-authored over 350 research publications in these areas, which have appeared in international journals, book chapters, and conference proceedings. He has served as the principal investigator or co-investigator in several R&D projects. He has (co-)edited over 40 international volumes. He is the editor-in-chief of the Intelligent Decision Technologies Journal (IOS Press). During 2012-2022, he was the editor-in-chief of the International Journal of Computational Intelligence Studies (Inderscience). He has been the editor-in-chief of the Engineering Section of SpringerPlus. He is the founder and editor-in-chief of the Learning and Analytics in Intelligent Systems book series (Springer 2019-) and the Artificial Intelligence-Enhanced Software and Systems Engineering book series (Springer 2022-). He has guest (co-)edited 17 special issues of international journals. He is a co-founder of the Information, Intelligence, Systems and Applications (IISA) conference series, technically sponsored by IEEE and currently in its 15th edition. He has organized and chaired over 40 international conferences. He has received best paper awards from several international conferences, and he has been a keynote speaker of several international conferences.

MARIA VIRVOU is a FULL PROFESSOR, HEAD OF THE DEPARTMENT, DIRECTOR OF POST- GRADUATE STUDIES and DIRECTOR OF THE SOFTWARE ENGINEERING LAB in the Department of Informatics, University of Piraeus, Greece. She received a B.Sc. Degree in Mathematics from the National and Kapodistrian University of Athens, Greece, a M.Sc. Degree in Computer Science from the University College London (UCL), U.K. and a Ph.D. Degree in Computer Science and Artificial Intelligence from the University of Sussex, U.K. funded by a scholarship obtained from the Greek State Scholarship Foundation. She is AUTHOR/CO-AUTHOR of over 350 research papers published in international journals, books and conference proceedings and of 7 books and monographs in Computer Science published by Springer and other publishers. She is currently CO-EDITOR of the Springer book series "Learning and Analytics in Intelligent Systems" and "Artificial Intelligence-Enhanced Software and Systems Engineering". She has been EDITOR of over 20 collections of papers in conference proceedings or books, published by major academic publishers, such as IEEE, Springer and IOS Press. She has also been EDITOR-IN-CHIEF of the SpringerPlus Journal (Springer) for the whole area of Computer Science and an ASSOCIATE EDITOR of many other journals. She was GENERAL CO-CHAIR of the yearly conference series of International

Inhalt

1. Introduction to advances in artificial intelligence-empowered decision support systems.- 2. Artificial Intelligence in Breast Cancer Diagnosis: A Review.- 3. Classification of H&E stained Liver Histopathology Images Using Ensemble Learning Techniques for detection of the level of malignancy of Hepatocellular Carcinoma (HCC).- 4. Performance Analysis of Deep Learning Models on Chemokines Protein Group Using Structure-Based Pattern Detection.- 5. Dynamic and Personalized Access Control to Electronic Health Records.