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245 1 0 _aAdvances in Artificial Intelligence-Empowered Decision Support Systems
_h[electronic resource] :
_bPapers in Honour of Professor John Psarras /
_cedited by George A. Tsihrintzis, Maria Virvou, Haris Doukas, Lakhmi C. Jain.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXV, 438 p. 191 illus., 134 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLearning and Analytics in Intelligent Systems,
_x2662-3455 ;
_v39
505 0 _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.
520 _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.
541 _fUABC ;
_cPerpetuidad
650 0 _aComputational intelligence.
650 0 _aMachine learning.
650 1 4 _aComputational Intelligence.
650 2 4 _aMachine Learning.
700 1 _aTsihrintzis, George A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aVirvou, Maria.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aDoukas, Haris.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aJain, Lakhmi C.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031623158
776 0 8 _iPrinted edition:
_z9783031623172
776 0 8 _iPrinted edition:
_z9783031623189
830 0 _aLearning and Analytics in Intelligent Systems,
_x2662-3455 ;
_v39
856 4 0 _zLibro electrónico
_uhttp://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-62316-5
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