03867nam a22005415i 4500 978-3-031-55865-8 DE-He213 20251030112304.0 cr nn 008mamaa 240608s2024 sz | s |||| 0|eng d 9783031558658 978-3-031-55865-8 10.1007/978-3-031-55865-8 doi R858-859.7 MBG bicssc UB bicssc MED117000 bisacsh UXT thema Natural Language Processing in Biomedicine [electronic resource] : A Practical Guide / edited by Hua Xu, Dina Demner Fushman. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XVI, 444 p. 75 illus., 42 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Cognitive Informatics in Biomedicine and Healthcare, 2662-7299 Introduction -- 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. This 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. Medical informatics. 60693 Psycholinguistics. 72377 Health Informatics. Language Processing. 78450 Xu, Hua. editor. edt http://id.loc.gov/vocabulary/relators/edt 70439 Demner Fushman, Dina. editor. edt http://id.loc.gov/vocabulary/relators/edt 78451 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031558641 Printed edition: 9783031558665 Printed edition: 9783031558672 Cognitive Informatics in Biomedicine and Healthcare, 2662-7299 78452 https://doi.org/10.1007/978-3-031-55865-8 ZDB-2-SME ZDB-2-SXM 60609 60609