LEADER 04158nam 22005535 450 001 9910869156303321 005 20251113184216.0 010 $a3-031-62316-9 024 7 $a10.1007/978-3-031-62316-5 035 $a(MiAaPQ)EBC31505438 035 $a(Au-PeEL)EBL31505438 035 $a(CKB)32575352900041 035 $a(DE-He213)978-3-031-62316-5 035 $a(EXLCZ)9932575352900041 100 $a20240627d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvances in Artificial Intelligence-Empowered Decision Support Systems $ePapers in Honour of Professor John Psarras /$fedited by George A. Tsihrintzis, Maria Virvou, Haris Doukas, Lakhmi C. Jain 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (439 pages) 225 1 $aLearning and Analytics in Intelligent Systems,$x2662-3455 ;$v39 311 08$a3-031-62315-0 327 $a1. 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. 330 $aDecision Support Systems (DSSs) are Software and Information Systems which make use of various data and business models, employ advanced data analytics procedures, and access extensive databases and data warehouses to facilitate with a decision process or with organizational issues. DSSs have proven to be particularly useful at the strategic level, while they usually require only limited computer-proficiency skills from their users. Although DSSs have been under development and use for several decades, recent advances in both Software Engineering technologies and Artificial Intelligence (AI) methodologies have heralded new avenues for research and development in this field. This book exposes its readers to some of the most significant Advances in Artificial Intelligence-Empowered Decision Support Systems. It consists of an editorial note and an additional sixteen (16) chapters, all invited from authors who work on the corresponding chapter theme and are recognized for their significant research contributions. The chapters are organized into five parts, namely (i) AI-Empowered DSS in Medical Diagnosis and Biology, (ii) AI-Empowered DSS in Healthcare and Health Insurance, (iii) AI-Empowered DSS in Urban Matters, (iv) Various Applications of AI-Empowered DSS, and (v) Novel AI-Empowered Methodologies in Decision Making. Targeted toward academics, researchers, practitioners, and students in Computer Science, Artificial Intelligence, and Management, this book is also accessible to individuals from other disciplines interested in the cutting-edge developments of AI-empowered DSS technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe deeper into the application areas of interest to them. 410 0$aLearning and Analytics in Intelligent Systems,$x2662-3455 ;$v39 606 $aComputational intelligence 606 $aMachine learning 606 $aComputational Intelligence 606 $aMachine Learning 615 0$aComputational intelligence. 615 0$aMachine learning. 615 14$aComputational Intelligence. 615 24$aMachine Learning. 676 $a006.3 700 $aTsihrintzis$b George A$0739887 701 $aVirvou$b Maria$0720958 701 $aDoukas$b Haris$01253627 701 $aJain$b L. C$01601441 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910869156303321 996 $aAdvances in Artificial Intelligence-Empowered Decision Support Systems$94521048 997 $aUNINA