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[null,"1.","Record Nr.",null,"UNINA9910452996403321"]
[null,null,"Autore",null,"Burrow J. A (John Anthony)"]
[null,null,"Titolo",null,"Medieval writers and their work [[electronic resource] ] : Middle English literature 1100-1500 / / J.A. Burrow"]
[null,null,"Pubbl/distr/stampa",null,"Oxford ; ; New York, : Oxford University Press, c2008"]
[null,null,"ISBN",null,"1-281-82565-4"]
[{"$nulls":4},"9786611825652"]
[{"$nulls":4},"0-19-153854-X"]
[null,null,"Edizione",null,"[2nd ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (165 p.)"]
[null,null,"Disciplina",null,"820/.9/001"]
[null,null,"Soggetti",null,"English literature - Middle English, 1100-1500 - History and criticism"]
[{"$nulls":4},"Civilization, Medieval, in literature"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","First published 1982."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references (p. [139]-151) and index."]
[null,null,"Nota di contenuto",null,"Contents; 1 The period and the literature; 2 Writers, audiences, and readers; 3 Major genres; 4 Modes of meaning; 5 The afterlife of Middle English literature; Notes; Bibliography; Index"]
[null,null,null,"Sommario/riassunto","A fully updated second edition of J. A. Burrow's hugely successful introduction to medieval English literature. - ;In an updated edition of his hugely successful student introduction to English literature from 1100 to 1500, J. A. Burrow takes account of scholarly developments in the field, most notably devoting a final chapter to the impact of historicism on medieval studies. Full of information and stimulating ideas, and a pleasure to read, Burrow's book deals with circumstances of composition and reception, the main genres, 'modes of meaning' (allegory etc.), and medieval literature's afterlife in modern times. It shows that the literature of authors such as Chaucer, Gower, and Langland is more readily accessible than usually imagined, and well worth reading too. By placing medieval writers in their historical context - the four centuries between the Norman Conquest and the Renaissance - Professor Burrow explains not only how they wrote, but why."]
[null,"2.","Record Nr.",null,"UNINA9911047821403321"]
[null,null,"Autore",null,"Nag Anindya"]
[null,null,"Titolo",null,"Feature Fusion for Next-Generation AI : Building Intelligent Solutions from Medical Data / / edited by Anindya Nag, Md. Mehedi Hassan, Anupam Kumar Bairagi"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026"]
[null,null,"ISBN",null,"3-031-94386-4"]
[null,null,"Edizione",null,"[1st ed. 2026.]"]
[null,null,"Descrizione fisica",null,"1 online resource (405 pages)"]
[null,null,"Collana",null,"Sustainable Artificial Intelligence-Powered Applications, IEREK Interdisciplinary Series for Sustainable Development, , 3005-1770"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Biomedical engineering"]
[{"$nulls":4},"Quantitative research"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Medical and Health Technologies"]
[{"$nulls":4},"Data Analysis and Big Data"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Fundamental Principles of Feature Fusion in Medical AI -- Data Preprocessing for Feature Synthesis in Medical AI -- Techniques for Selecting Features in Medical Data -- Dimensionality Reduction Techniques: Foundations and Applications in Medical Data Analysis -- Meta-Heuristic Algorithms for High-Dimensional Feature Selection."]
[null,null,null,"Sommario/riassunto","This book delves into the fundamental concepts, methodologies, and practical implementations of feature fusion, providing valuable perspectives on how merging several data aspects might augment the decision-making skills of artificial intelligence. Feature fusion is inherently connected to the advancement of intelligent solutions from medical data as it enables the incorporation of various and complementary data sources to construct more advanced AI models. Within the medical domain, data manifests in diverse formats, including electronic health records (EHRs), medical imaging, genomic data, and real-time sensor metrics. Although each of these data kinds offers distinct perspectives, they may have limitations in terms of their breadth or depth when considered independently. The application of feature fusion enables the integration of diverse data sources into a unified model, hence improving the AI's capacity to detect patterns, "]
[{"$nulls":4},"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."]