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Biomedical Natural Language Processing

Biomedical Natural Language Processing
Author: Kevin Bretonnel Cohen
Publisher: John Benjamins Publishing Company
Total Pages: 174
Release: 2014-02-15
Genre: Computers
ISBN: 9027271062

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Biomedical Natural Language Processing is a comprehensive tour through the classic and current work in the field. It discusses all subjects from both a rule-based and a machine learning approach, and also describes each subject from the perspective of both biological science and clinical medicine. The intended audience is readers who already have a background in natural language processing, but a clear introduction makes it accessible to readers from the fields of bioinformatics and computational biology, as well. The book is suitable as a reference, as well as a text for advanced courses in biomedical natural language processing and text mining.


Natural Language Processing in Biomedicine

Natural Language Processing in Biomedicine
Author: Hua Xu
Publisher: Springer
Total Pages: 0
Release: 2024-05-27
Genre: Medical
ISBN: 9783031558641

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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.


Statistical Language Learning

Statistical Language Learning
Author: Eugene Charniak
Publisher: MIT Press
Total Pages: 196
Release: 1996
Genre: Computers
ISBN: 9780262531412

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This text introduces statistical language processing techniques--word tagging, parsing with probabilistic context free grammars, grammar induction, syntactic disambiguation, semantic word classes, word-sense disambiguation--along with the underlying mathematics and chapter exercises.


Methods in Biomedical Informatics

Methods in Biomedical Informatics
Author: Indra Neil Sarkar
Publisher: Academic Press
Total Pages: 589
Release: 2013-09-03
Genre: Computers
ISBN: 0124016847

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Beginning with a survey of fundamental concepts associated with data integration, knowledge representation, and hypothesis generation from heterogeneous data sets, Methods in Biomedical Informatics provides a practical survey of methodologies used in biological, clinical, and public health contexts. These concepts provide the foundation for more advanced topics like information retrieval, natural language processing, Bayesian modeling, and learning classifier systems. The survey of topics then concludes with an exposition of essential methods associated with engineering, personalized medicine, and linking of genomic and clinical data. Within an overall context of the scientific method, Methods in Biomedical Informatics provides a practical coverage of topics that is specifically designed for: (1) domain experts seeking an understanding of biomedical informatics approaches for addressing specific methodological needs; or (2) biomedical informaticians seeking an approachable overview of methodologies that can be used in scenarios germane to biomedical research. Contributors represent leading biomedical informatics experts: individuals who have demonstrated effective use of biomedical informatics methodologies in the real-world, high-quality biomedical applications Material is presented as a balance between foundational coverage of core topics in biomedical informatics with practical "in-the-trenches" scenarios. Contains appendices that function as primers on: (1) Unix; (2) Ruby; (3) Databases; and (4) Web Services.


Medical Language Processing

Medical Language Processing
Author: Naomi Sager
Publisher: Addison Wesley Publishing Company
Total Pages: 382
Release: 1987
Genre: Computers
ISBN:

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Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics
Author: Basant Agarwal
Publisher: Academic Press
Total Pages: 367
Release: 2020-01-14
Genre: Science
ISBN: 0128190620

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Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis


The Form of Information in Science

The Form of Information in Science
Author: Z. Harris
Publisher: Springer Science & Business Media
Total Pages: 622
Release: 1988-12-31
Genre: Philosophy
ISBN: 9789027725165

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DOES DISCOURSE HAVE A 'STRUCTURE'? HARRIS'S REVOLUTION IN LINGUISTICS As a freshman back in 1947 I discovered that within the various academic divisions and subdivisions of the University of Pennsylvania there existed a something (it was not a Department, but a piece of the Anthropology Department) called 'Linguistic Analysis'. I was an untalented but enthusiastic student of Greek and a slightly more talented student of German, as well as the son of a translator, so the idea of 'Linguistic Analysis' attracted me, sight unseen, and I signed up for a course. It turned out that 'Linguistic Analysis' was essentially a graduate program - I and another undergraduate called Noam Chomsky were the only two undergraduates who took courses in Linguistic Analysis - and also that it was essentially a one-man show: a professor named Zellig Harris taught all the courses with the aid of graduate Teaching Fellows (and possibly - I am not sure - one Assistant Professor). The technicalities of Linguistic Analysis were formidable, and I never did master them all. But the powerful intellect and personality of Zellig Harris drew me like a lodestone, and, although I majored in Philosophy, I took every course there was to take in Linguistic Analysis from then until my gradua tion. What 'Linguistics' was like before Zellig Harris is something not many people care to remember today.


Clinical Text Mining

Clinical Text Mining
Author: Hercules Dalianis
Publisher: Springer
Total Pages: 192
Release: 2018-05-14
Genre: Computers
ISBN: 3319785036

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This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.


Information Retrieval in Biomedicine: Natural Language Processing for Knowledge Integration

Information Retrieval in Biomedicine: Natural Language Processing for Knowledge Integration
Author: Prince, Violaine
Publisher: IGI Global
Total Pages: 460
Release: 2009-03-31
Genre: Computers
ISBN: 1605662755

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"This book provides relevant theoretical frameworks and the latest empirical research findings in biomedicine information retrieval as it pertains to linguistic granularity"--Provided by publisher.