Text mining web based medical (23 Ergebnisse)

Hardcover. Zustand: Good Plus. [TECHNOLOGY]. Ed. Amy Neustein. Contributors: Johan Gustav Bellika, Angel Bravo-Salgado, et al. "Text Mining of Web-Based Medical Content: Speech Technology and Text Mining in Medicine and Health Care [Signed]." Boston and Berlin: Walter de Gruyter, Inc., 2014. English language. Hardcover. Text with charts and full-color illustrations. A collection of academic articles. Price in pencil on free front endpaper. Text clean. Faint tidelines at interior of back gutter. Good Plus. ISBN: 9781614515418. ISSN: 2329-5198. "Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information.". Signed.…

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,500grams, ISBN:9781614515418. …

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Hardback. Zustand: New. New copy - Usually dispatched within 4 working days.

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Hardcover. Zustand: Brand New. 284 pages. 9.60x6.50x1.10 inches. In Stock.

Hardback. Zustand: New. . Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature. Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing. Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include. Clinical Documents in Electronic Health Records. Summarization Techniques for Online Health Data. Natural Language Processing for Text Mining. Query Expansion Techniques for Tweets. Online Video Data Retrieval of Health-Related Videos. Dengue Fever Outbreaks. Bioemergencies and Social Media Posts. Speech-based Disease Screening for Malaria, Yellow Fever, Typhoid, and Lassa Fever. Audio Access to Online Video Data for the Visually Impaired.…

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Zustand: New. 2014. Hardcover. . . . . .

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - - Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature.- Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing.- Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include:- Mining Biomedical Literature and Clinical Narratives - Medication Information Extraction - Machine Learning Techniques for Mining Medical Search Queries - Detecting the Level of Personal Health Information Revealed in Social Media - Curating Layperson's Personal Experiences with Health Care from Social Media and Twitter - Health Dialogue Systems for Improving Access to Online Content - Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired - Semantic-based Visual Information Retrieval for Mining Radiographic Image Data - Evaluating the Importance of Medical Terminology in YouTube Video Titles and Descriptions ; - Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature.- Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing.- Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include:- Clinical Documents in Electronic Health Records- Summarization Techniques for Online Health Data- Natural Language Processing for Text Mining- Query Expansion Techniques for Tweets- Online Video Data Retrieval of Health-Related Videos- Dengue Fever Outbreaks- Bioemergencies and Social Media Posts- Speech-based Disease Screening for Malaria, Yellow Fever, Typhoid, and Lassa Fever- Audio Access to Online Video Data for the Visually Impaired.…

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 286 | Sprache: Englisch | Produktart: Bücher | • Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature. • Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing. • Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include: • Mining Biomedical Literature and Clinical Narratives • Medication Information Extraction • Machine Learning Techniques for Mining Medical Search Queries • Detecting the Level of Personal Health Information Revealed in Social Media • Curating Layperson's Personal Experiences with Health Care from Social Media and Twitter • Health Dialogue Systems for Improving Access to Online Content • Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired • Semantic-based Visual Information Retrieval for Mining Radiographic Image Data • Evaluating the Importance of Medical Terminology in YouTube Video Titles and Descriptions.…

Zustand: New. 2014. Hardcover. . . . . . Books ship from the US and Ireland.

Hardback. Zustand: New. . Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature. Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing. Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include. Clinical Documents in Electronic Health Records. Summarization Techniques for Online Health Data. Natural Language Processing for Text Mining. Query Expansion Techniques for Tweets. Online Video Data Retrieval of Health-Related Videos. Dengue Fever Outbreaks. Bioemergencies and Social Media Posts. Speech-based Disease Screening for Malaria, Yellow Fever, Typhoid, and Lassa Fever. Audio Access to Online Video Data for the Visually Impaired.…

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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -- Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature.- Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing.- Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include:- Mining Biomedical Literature and Clinical Narratives - Medication Information Extraction - Machine Learning Techniques for Mining Medical Search Queries - Detecting the Level of Personal Health Information Revealed in Social Media - Curating Layperson's Personal Experiences with Health Care from Social Media and Twitter - Health Dialogue Systems for Improving Access to Online Content - Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired - Semantic-based Visual Information Retrieval for Mining Radiographic Image Data - Evaluating the Importance of Medical Terminology in YouTube Video Titles and Descriptions ; - Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature.- Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing.- Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include:- Clinical Documents in Electronic Health Records- Summarization Techniques for Online Health Data- Natural Language Processing for Text Mining- Query Expansion Techniques for Tweets- Online Video Data Retrieval of Health-Related Videos- Dengue Fever Outbreaks- Bioemergencies and Social Media Posts- Speech-based Disease Screening for Malaria, Yellow Fever, Typhoid, and Lassa Fever- Audio Access to Online Video Data for the Visually Impaired 286 pp. Englisch.…

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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. - Includes Text Mining and Natural Lan.

Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware - Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature. Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing. Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired.Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information.This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers.Topics in this book include: Mining Biomedical Literature and Clinical Narratives Medication Information Extraction Machine Learning Techniques for Mining Medical Search Queries Detecting the Level of Personal Health Information Revealed in Social Media Curating Layperson's Personal Experiences with Health Care from Social Media and Twitter Health Dialogue Systems for Improving Access to Online Content Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired Semantic-based Visual Information Retrieval for Mining Radiographic Image Data Evaluating the Importance of Medical Terminology in YouTube Video Titles and DescriptionsDe Gruyter Mouton, Genthiner Straße 13, 10785 Berlin 286 pp. Englisch. …