LEADER 01160nam a2200253 i 4500 001 991003403469707536 005 20020503191452.0 008 000704s1967 uk ||| | eng 035 $ab1050056x-39ule_inst 035 $aEXGIL120231$9ExL 040 $aBiblioteca Interfacoltà$bita 100 1 $aCaxton, William$0196637 245 14$aThe lyf of the noble and Crysten prynce, Charles the Grete :$btranslated from the French by William Caxton and printed by him 1485 :$bedited from the unique copy in the British Museum /$cby Sidney J. H. Herrtage 260 $aLondon :$bOxford University Press,$c[1967] 300 $aXII, 268 p. ;$c23 cm. 440 4$aThe english Charlemagne romances ;$v3-4 490 0 $aEarly English Text Society. Extra series ;$v36-37 700 1 $aHerrtage, Sidney John Hervon 907 $a.b1050056x$b21-02-17$c27-06-02 912 $a991003403469707536 945 $aLE002 In. III L 14$cV. 3-4$g1$i2002000923875$lle002$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i10577300$z27-06-02 996 $aLyf of the noble and Crysten prynce, Charles the Grete$9212316 997 $aUNISALENTO 998 $ale002$b01-01-00$cm$da $e-$feng$guk $h4$i1 LEADER 04712nam 22007215 450 001 9910483376403321 005 20251113181706.0 010 $a3-030-33966-1 024 7 $a10.1007/978-3-030-33966-1 035 $a(CKB)4100000009844795 035 $a(MiAaPQ)EBC5979117 035 $a(DE-He213)978-3-030-33966-1 035 $z(PPN)258866721 035 $a(PPN)243767676 035 $a(EXLCZ)994100000009844795 100 $a20191114d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep Learning Techniques for Biomedical and Health Informatics /$fedited by Sujata Dash, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, Arpad Kelemen 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (395 pages) 225 1 $aStudies in Big Data,$x2197-6511 ;$v68 311 08$a3-030-33965-3 327 $aMedNLU: Natural Language Understander for Medical Texts -- Deep Learning Based Biomedical Named Entity Recognition Systems -- Disambiguation Model for Bio-Medical Named Entity Recognition -- Applications of Deep Learning in Healthcare and Biomedicine -- Deep Learning for Clinical Decision Support Systems: A Review from the Panorama of Smart Healthcare -- Review of Machine Learning and Deep Learning based Recommender Systems for Health Informatics -- Deep Learning and Explainable AI in Healthcare using EHR -- Deep Learning for Analysis of Electronic Heath Records -- Bioinformatics Using Deep Architecture -- Intelligent, Secure Big Health Data Management using Deep Learning and Blockchain Technology: An Overview -- Malaria Disease Detection using CNN Technique with SGD, RMSprop and ADAM Optimizers -- Deep Reinforcement Learning based Personalized Health Recommendations. 330 $aThis book presents a collection of state-of-the-art approaches for deep-learning-based biomedical and health-related applications. The aim of healthcare informatics is to ensure high-quality, efficient health care, and better treatment and quality of life by efficiently analyzing abundant biomedical and healthcare data, including patient data and electronic health records (EHRs), as well as lifestyle problems. In the past, it was common to have a domain expert to develop a model for biomedical or health care applications; however, recent advances in the representation of learning algorithms (deep learning techniques) make it possible to automatically recognize the patterns and represent the given data for the development of such model. This book allows new researchers and practitioners working in the field to quickly understand the best-performing methods. It also enables them to compare different approaches and carry forward their research in an important area that has a direct impact on improving the human life and health. It is intended for researchers, academics, industry professionals, and those at technical institutes and R&D organizations, as well as students working in the fields of machine learning, deep learning, biomedical engineering, health informatics, and related fields. . 410 0$aStudies in Big Data,$x2197-6511 ;$v68 606 $aComputational intelligence 606 $aEngineering$xData processing 606 $aBiomedical engineering 606 $aBig data 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aData Engineering 606 $aBiomedical Engineering and Bioengineering 606 $aBig Data 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aEngineering$xData processing. 615 0$aBiomedical engineering. 615 0$aBig data. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aData Engineering. 615 24$aBiomedical Engineering and Bioengineering. 615 24$aBig Data. 615 24$aArtificial Intelligence. 676 $a006.31 702 $aDash$b Sujata$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAcharya$b Biswa Ranjan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aMittal$b Mamta$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAbraham$b Ajith$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKelemen$b Arpad$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483376403321 996 $aDeep Learning Techniques for Biomedical and Health Informatics$92853799 997 $aUNINA