LEADER 04097nam 22005535 450 001 9910746284503321 005 20230918061212.0 010 $a3-031-25928-9 024 7 $a10.1007/978-3-031-25928-9 035 $a(CKB)28278055300041 035 $a(DE-He213)978-3-031-25928-9 035 $a(PPN)272738301 035 $a(MiAaPQ)EBC31052664 035 $a(Au-PeEL)EBL31052664 035 $a(EXLCZ)9928278055300041 100 $a20230915d2023 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aIntroduction to Artificial Intelligence$b[electronic resource] /$fedited by Michail E. Klontzas, Salvatore Claudio Fanni, Emanuele Neri 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (VIII, 165 p. 21 illus., 20 illus. in color.) 225 1 $aImaging Informatics for Healthcare Professionals,$x2662-155X 311 $a9783031259272 327 $aWhat is Artificial Intelligence: History and Basic Definitions -- Programming Languages and Tools Used for AI Applications -- Introduction to Traditional Machine Learning -- Machine Learning Methods for Radiomics Analysis -- Natural Language Processing (NLP) -- Deep Learning -- Data Preparation for AI Purposes -- Current Applications of AI in Medical Imaging. . 330 $aThis book aims to provide physicians and scientists with the basics of Artificial Intelligence (AI) with a special focus on medical imaging. The contents of the book provide an introduction to the main topics of artificial intelligence currently applied on medical image analysis. The book starts with a chapter explaining the basic terms used in artificial intelligence for novice readers and embarks on a series of chapters each one of which provides the basics on one AI-related topic. The second chapter presents the programming languages and available automated tools that enable the development of AI applications for medical imaging. The third chapter endeavours to analyse the main traditional machine learning techniques, explaining algorithms such as random forests, support vector machines as well as basic neural networks. The applications of those machines on the analysis of radiomics data is expanded in the fourth chapter to allow the understanding of algorithms used to build classifiers for the diagnosis of disease processes with the use of radiomics. Chapter five provides the basics of natural language processing which has revolutionized the analysis of complex radiological reports and chapter six affords a succinct introduction to convolutional neural networks which have revolutionized medical image analysis enabling automated image-based diagnosis, image enhancement (e.g. denoising), protocolling etc. The penultimate chapter provides an introduction to data preprocessing for use in the aforementioned artificial intelligence applications. The book concludes with a chapter demonstrating AI-based tools already in radiological practice while providing an insight about the foreseeable future. It will be a valuable resource for radiologists, computer scientists and postgraduate students working on medical image analysis. 410 0$aImaging Informatics for Healthcare Professionals,$x2662-155X 606 $aRadiology 606 $aMedical informatics 606 $aRadiology 606 $aHealth Informatics 615 0$aRadiology. 615 0$aMedical informatics. 615 14$aRadiology. 615 24$aHealth Informatics. 676 $a616.0757 702 $aKlontzas$b Michail E$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aFanni$b Salvatore Claudio$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aNeri$b Emanuele$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910746284503321 996 $aIntroduction to Artificial Intelligence$93568956 997 $aUNINA