Natural Language Processing in Biomedicine
Author : Hua Xu
Publisher : Springer Nature
Page : 449 pages
File Size : 35,48 MB
Release :
Category :
ISBN : 3031558650
Biomedical Natural Language Processing
Author : Kevin Bretonnel Cohen
Publisher : John Benjamins Publishing Company
Page : 174 pages
File Size : 31,2 MB
Release : 2014-02-15
Category : Computers
ISBN : 9027271062
Book Description
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.
Statistical Language Learning
Author : Eugene Charniak
Publisher : MIT Press
Page : 196 pages
File Size : 32,61 MB
Release : 1996
Category : Computers
ISBN : 9780262531412
Book Description
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.
Medical Language Processing
Author : Naomi Sager
Publisher : Addison Wesley Publishing Company
Page : 382 pages
File Size : 28,44 MB
Release : 1987
Category : Computers
ISBN :
Book Description
Methods in Biomedical Informatics
Author : Indra Neil Sarkar
Publisher : Academic Press
Page : 589 pages
File Size : 21,95 MB
Release : 2013-09-03
Category : Computers
ISBN : 0124016847
Book Description
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.
Biomedical Information Technology
Author : David Dagan Feng
Publisher : Academic Press
Page : 822 pages
File Size : 34,18 MB
Release : 2019-10-22
Category : Science
ISBN : 0128160357
Book Description
Biomedical Information Technology, Second Edition, contains practical, integrated clinical applications for disease detection, diagnosis, surgery, therapy and biomedical knowledge discovery, including the latest advances in the field, such as biomedical sensors, machine intelligence, artificial intelligence, deep learning in medical imaging, neural networks, natural language processing, large-scale histopathological image analysis, virtual, augmented and mixed reality, neural interfaces, and data analytics and behavioral informatics in modern medicine. The enormous growth in the field of biotechnology necessitates the utilization of information technology for the management, flow and organization of data. All biomedical professionals can benefit from a greater understanding of how data can be efficiently managed and utilized through data compression, modeling, processing, registration, visualization, communication and large-scale biological computing. - Presents the world's most recognized authorities who give their "best practices" - Provides professionals with the most up-to-date and mission critical tools to evaluate the latest advances in the field - Gives new staff the technological fundamentals and updates experienced professionals with the latest practical integrated clinical applications
The Form of Information in Science
Author : Z. Harris
Publisher : Springer Science & Business Media
Page : 622 pages
File Size : 21,40 MB
Release : 1988-12-31
Category : Philosophy
ISBN : 9789027725165
Book Description
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
Author : Hercules Dalianis
Publisher : Springer
Page : 192 pages
File Size : 27,16 MB
Release : 2018-05-14
Category : Computers
ISBN : 3319785036
Book Description
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.
Deep Learning Techniques for Biomedical and Health Informatics
Author : Basant Agarwal
Publisher : Academic Press
Page : 370 pages
File Size : 32,98 MB
Release : 2020-01-14
Category : Science
ISBN : 0128190620
Book Description
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
Sex and Gender Bias in Technology and Artificial Intelligence
Author : Davide Cirillo
Publisher : Academic Press
Page : 280 pages
File Size : 24,85 MB
Release : 2022-05-21
Category : Medical
ISBN : 0128213930
Book Description
Sex and Gender Bias in Technology and Artificial Intelligence: Biomedicine and Healthcare Applications details the integration of sex and gender as critical factors in innovative technologies (artificial intelligence, digital medicine, natural language processing, robotics) for biomedicine and healthcare applications. By systematically reviewing existing scientific literature, a multidisciplinary group of international experts analyze diverse aspects of the complex relationship between sex and gender, health and technology, providing a perspective overview of the pressing need of an ethically-informed science. The reader is guided through the latest implementations and insights in technological areas of accelerated growth, putting forward the neglected and overlooked aspects of sex and gender in biomedical research and healthcare solutions that leverage artificial intelligence, biosensors, and personalized medicine approaches to predict and prevent disease outcomes. The reader comes away with a critical understanding of this fundamental issue for the sake of better future technologies and more effective clinical approaches. - First comprehensive title addressing the topic of sex and gender biases and artificial intelligence applications to biomedical research and healthcare - Co-published by the Women's Brain Project, a leading non-profit organization in this area - Guides the reader through important topics like the Generation of Clinical Data, Clinical Trials, Big Data Analytics, Digital Biomarkers, Natural Language Processing
