03983nam 22006615 450 991048385140332120200702040542.03-030-42750-110.1007/978-3-030-42750-4(CKB)4100000011232686(MiAaPQ)EBC6200126(DE-He213)978-3-030-42750-4(PPN)248395432(EXLCZ)99410000001123268620200515d2020 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierDeep Learners and Deep Learner Descriptors for Medical Applications /edited by Loris Nanni, Sheryl Brahnam, Rick Brattin, Stefano Ghidoni, Lakhmi C. Jain1st ed. 2020.Cham :Springer International Publishing :Imprint: Springer,2020.1 online resource (286 pages)Intelligent Systems Reference Library,1868-4394 ;1863-030-42748-X Includes bibliographical references.This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications. It reviews the recent literature and presents a variety of medical image and sound applications to illustrate the five major ways deep learners can be utilized: 1) by training a deep learner from scratch (chapters provide tips for handling imbalances and other problems with the medical data); 2) by implementing transfer learning from a pre-trained deep learner and extracting deep features for different CNN layers that can be fed into simpler classifiers, such as the support vector machine; 3) by fine-tuning one or more pre-trained deep learners on an unrelated dataset so that they are able to identify novel medical datasets; 4) by fusing different deep learner architectures; and 5) by combining the above methods to generate a variety of more elaborate ensembles. This book is a value resource for anyone involved in engineering deep learners for medical applications as well as to those interested in learning more about the current techniques in this exciting field. A number of chapters provide source code that can be used to investigate topics further or to kick-start new projects. .Intelligent Systems Reference Library,1868-4394 ;186Computational intelligenceArtificial intelligenceHealth informaticsBiomedical engineeringComputational Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/T11014Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Health Informaticshttps://scigraph.springernature.com/ontologies/product-market-codes/I23060Biomedical Engineering and Bioengineeringhttps://scigraph.springernature.com/ontologies/product-market-codes/T2700XComputational intelligence.Artificial intelligence.Health informatics.Biomedical engineering.Computational Intelligence.Artificial Intelligence.Health Informatics.Biomedical Engineering and Bioengineering.610.28Nanni Lorisedthttp://id.loc.gov/vocabulary/relators/edtBrahnam Sheryledthttp://id.loc.gov/vocabulary/relators/edtBrattin Rickedthttp://id.loc.gov/vocabulary/relators/edtGhidoni Stefanoedthttp://id.loc.gov/vocabulary/relators/edtJain Lakhmi Cedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910483851403321Deep Learners and Deep Learner Descriptors for Medical Applications2846134UNINA