03544nam a22004575i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001500153072001600168072001500184072002300199072001500222245013300237250001800370264007500388300006500463336002600528337002600554338003600580347002400616490006800640505045700708520138901165650002502554650002302579650002402602650002502626700007002651700008302721710003402804773002602838776003602864776003602900776003602936830006802972856004603040978-3-031-55865-8DE-He21320251030112304.0cr nn 008mamaa240608s2024    sz |    s    |||| 0|eng d  a97830315586587 a10.1007/978-3-031-55865-82doi 4aR858-859.7 7aMBG2bicssc 7aUB2bicssc 7aMED1170002bisacsh 7aUXT2thema10aNatural Language Processing in Biomedicineh[electronic resource] :bA Practical Guide /cedited by Hua Xu, Dina Demner Fushman.  a1st ed. 2024. 1aCham :bSpringer International Publishing :bImprint: Springer,c2024.  aXVI, 444 p. 75 illus., 42 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aCognitive Informatics in Biomedicine and Healthcare,x2662-72990 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.  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. 0aMedical informatics. 0aPsycholinguistics.14aHealth Informatics.24aLanguage Processing.1 aXu, Hua.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt1 aDemner Fushman, Dina.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303155864108iPrinted edition:z978303155866508iPrinted edition:z9783031558672 0aCognitive Informatics in Biomedicine and Healthcare,x2662-729940uhttps://doi.org/10.1007/978-3-031-55865-8