LEADER 04364nam 22007455 450 001 9910483237803321 005 20200630120517.0 010 $a981-15-6325-X 024 7 $a10.1007/978-981-15-6325-6 035 $a(CKB)5310000000016619 035 $a(MiAaPQ)EBC6303660 035 $a(DE-He213)978-981-15-6325-6 035 $a(PPN)248595601 035 $a(EXLCZ)995310000000016619 100 $a20200617d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aDeep Learning for Medical Decision Support Systems /$fby Utku Kose, Omer Deperlioglu, Jafar Alzubi, Bogdan Patrut 205 $a1st ed. 2021. 210 1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2021. 215 $a1 online resource (xviii, 171 pages) $cillustrations 225 1 $aStudies in Computational Intelligence,$x1860-949X ;$v909 311 $a981-15-6324-1 327 $aDeep Learning for Innovative Medical Decision Support -- Deep Learning and Image Analysis for Medical Decision Support -- Deep Learning Oriented Systems for Medical Education -- Hybrid Deep Systems for Medical Education and Decision Support. 330 $aThis book explores various applications of deep learning-oriented diagnosis leading to decision support, while also outlining the future face of medical decision support systems. Artificial intelligence has now become a ubiquitous aspect of modern life, and especially machine learning enjoysgreat popularity, since it offers techniques that are capable of learning from samples to solve newly encountered cases. Today, a recent form of machine learning, deep learning, is being widely used with large, complex quantities of data, because today?s problems require detailed analyses of more data. This is critical, especially in fields such as medicine. Accordingly, the objective of this book is to provide the essentials of and highlight recent applications of deep learning architectures for medical decision support systems. The target audience includes scientists, experts, MSc and PhD students, postdocs, and any readers interested in the subjectsdiscussed. The book canbe used as a reference work to support courses on artificial intelligence, machine/deep learning, medical and biomedicaleducation. . 410 0$aStudies in Computational Intelligence,$x1860-949X ;$v909 606 $aComputational intelligence 606 $aMachine learning 606 $aHealth informatics 606 $aOptical data processing 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014 606 $aMachine Learning$3https://scigraph.springernature.com/ontologies/product-market-codes/I21010 606 $aHealth Informatics$3https://scigraph.springernature.com/ontologies/product-market-codes/H28009 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics$3https://scigraph.springernature.com/ontologies/product-market-codes/I22005 606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 615 0$aComputational intelligence. 615 0$aMachine learning. 615 0$aHealth informatics. 615 0$aOptical data processing. 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 14$aComputational Intelligence. 615 24$aMachine Learning. 615 24$aHealth Informatics. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aSignal, Image and Speech Processing. 676 $a610.28563 700 $aKose$b Utku$4aut$4http://id.loc.gov/vocabulary/relators/aut$01076791 702 $aDeperlioglu$b Omer$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aAlzubi$b Jafar$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aPatrut$b Bogdan$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483237803321 996 $aDeep Learning for Medical Decision Support Systems$92849661 997 $aUNINA