01168nam a2200265 i 4500991000237509707536040921s2002 gw 101 0 ger d3161477286 (pbk.)b1319415x-39ule_instDip.to Studi Giuridiciita340.11Responsive Regulierung :Beitrèage zur interdisziplinèaren Institutionenanalyse und Gesetzesfolgenabschèatzung /herausgegeben von Kilian Bizer, Martin Fuhr, Christoph HuttigTubingen :Mohr Siebeck,2002viii, 261 p. ;24 cmEffettività e validità della leggeCongressiLegislazioneCongressiBizer, Kilianauthorhttp://id.loc.gov/vocabulary/relators/aut737563Fuhr, Martinauthorhttp://id.loc.gov/vocabulary/relators/aut737564Huttig, Christoph.b1319415x02-04-1421-09-04991000237509707536LE027 340.11 BIZ01.011le027-E64.00-l- 00000.i1384712021-09-04Responsive Regulierung1460214UNISALENTOle02721-09-04ma -gergw 0004470nam 22006015 450 991104782140332120251127082722.03-031-94386-410.1007/978-3-031-94386-7(MiAaPQ)EBC32340636(Au-PeEL)EBL32340636(CKB)41603697900041(OCoLC)1545643832(DE-He213)978-3-031-94386-7(EXLCZ)994160369790004120251127d2026 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierFeature Fusion for Next-Generation AI Building Intelligent Solutions from Medical Data /edited by Anindya Nag, Md. Mehedi Hassan, Anupam Kumar Bairagi1st ed. 2026.Cham :Springer Nature Switzerland :Imprint: Springer,2026.1 online resource (405 pages)Sustainable Artificial Intelligence-Powered Applications, IEREK Interdisciplinary Series for Sustainable Development,3005-17703-031-94385-6 Fundamental Principles of Feature Fusion in Medical AI -- Data Preprocessing for Feature Synthesis in Medical AI -- Techniques for Selecting Features in Medical Data -- Dimensionality Reduction Techniques: Foundations and Applications in Medical Data Analysis -- Meta-Heuristic Algorithms for High-Dimensional Feature Selection.This book delves into the fundamental concepts, methodologies, and practical implementations of feature fusion, providing valuable perspectives on how merging several data aspects might augment the decision-making skills of artificial intelligence. Feature fusion is inherently connected to the advancement of intelligent solutions from medical data as it enables the incorporation of various and complementary data sources to construct more advanced AI models. Within the medical domain, data manifests in diverse formats, including electronic health records (EHRs), medical imaging, genomic data, and real-time sensor metrics. Although each of these data kinds offers distinct perspectives, they may have limitations in terms of their breadth or depth when considered independently. The application of feature fusion enables the integration of diverse data sources into a unified model, hence improving the AI's capacity to detect patterns, make precise predictions, and produce significant insights. The fusion process facilitates the development of intelligent solutions that exhibit enhanced reliability and effectiveness by using a more extensive reservoir of knowledge. For example, an artificial intelligence system that combines imaging data with clinical history might enhance the precision of disease diagnosis, forecast patient outcomes, and suggest tailored treatment strategies. Feature fusion is the crucial factor in unleashing the complete capabilities of medical data, enabling artificial intelligence to provide intelligent solutions that not only enhance the provision of healthcare but also stimulate advancements in medical research and practice. The proposed book explores the advanced notion of feature fusion within the field of artificial intelligence, with a particular emphasis on its implementation in physiological data. The integration of many data sources is crucial in the development of more precise, dependable, and understandable AI models as the healthcare industry becomes more data-driven.Sustainable Artificial Intelligence-Powered Applications, IEREK Interdisciplinary Series for Sustainable Development,3005-1770Artificial intelligenceBiomedical engineeringQuantitative researchArtificial IntelligenceMedical and Health TechnologiesData Analysis and Big DataArtificial intelligence.Biomedical engineering.Quantitative research.Artificial Intelligence.Medical and Health Technologies.Data Analysis and Big Data.006.3Nag Anindya999620Hassan Mehedi1833381Bairagi Anupam Kumar1862395MiAaPQMiAaPQMiAaPQBOOK9911047821403321Feature Fusion for Next-Generation AI4468645UNINA