LEADER 03702nam 22005535 450 001 9910865270903321 005 20251113183835.0 010 $a9783031558658$b(electronic bk.) 010 $z9783031558641 024 7 $a10.1007/978-3-031-55865-8 035 $a(MiAaPQ)EBC31460639 035 $a(Au-PeEL)EBL31460639 035 $a(CKB)32258753900041 035 $a(DE-He213)978-3-031-55865-8 035 $a(MiAaPQ)EBC31854766 035 $a(Au-PeEL)EBL31854766 035 $a(EXLCZ)9932258753900041 100 $a20240608d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNatural Language Processing in Biomedicine $eA Practical Guide /$fedited by Hua Xu, Dina Demner Fushman 205 $a1st ed. 2024. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2024. 215 $a1 online resource (449 pages) 225 1 $aCognitive Informatics in Biomedicine and Healthcare,$x2662-7299 311 08$aPrint version: Xu, Hua Natural Language Processing in Biomedicine Cham : Springer International Publishing AG,c2024 9783031558641 327 $aIntroduction -- Overview of linguistic information -- Deal with words -- Processing sentences -- Corpus analysis -- Machine learning and deep learning algorithms -- Named entity recognition -- Relation extraction -- Concept normalization (entity linking) -- Information retrieval -- Text classification -- Question answering -- Text generation -- Developing Biomedical NLP Systems -- NLP applications in healthcare -- NLP applications for life science. 330 $aThis textbook covers broad topics within the application of natural language processing (NLP) in biomedicine, and provides in-depth review of the NLP solutions that reveal information embedded in biomedical text. The need for biomedical NLP research and development has grown rapidly in the past two decades as an important field in cognitive informatics. Natural Language Processing in Biomedicine: A Practical Guide introduces the history of the biomedical NLP field and takes the reader through the basic aspects of NLP including different levels of linguistic information and widely used machine learning and deep learning algorithms. The book details common biomedical NLP tasks, such as named entity recognition, concept normalization, relation extraction, text classification, information retrieval, and question answering. The book illustrates the tasks with real-life use cases and introduces real-world datasets, novel machine learning and deep learning algorithms, and large language models. Relevant resources for corpora and medical terminologies are also introduced. The final chapters are devoted to discussing applications of biomedical NLP in healthcare and life sciences. This textbook therefore represents essential reading for students in biomedical informatics programs, as well as for professionals who are conducting research or building biomedical NLP systems. 410 0$aCognitive Informatics in Biomedicine and Healthcare,$x2662-7299 606 $aMedical informatics 606 $aPsycholinguistics 606 $aHealth Informatics 606 $aLanguage Processing 615 0$aMedical informatics. 615 0$aPsycholinguistics. 615 14$aHealth Informatics. 615 24$aLanguage Processing. 676 $a610,285 700 $aXu$b Hua$01669353 701 $aDemner-Fushman$b Dina$01671915 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910865270903321 996 $aNatural Language Processing in Biomedicine$94169573 997 $aUNINA