Sprache: Englisch
Verlag: Boston and Berlin: Walter de Gruyter, Inc., 2014
ISBN 10: 1614515417 ISBN 13: 9781614515418
Anbieter: James Payne, Books and Prints, New York City, NY, USA
Signiert
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.
Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
EUR 75,78
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In den WarenkorbZustand: 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.
Zustand: New.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 89,55
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In den WarenkorbZustand: New. In.
Zustand: As New. Unread book in perfect condition.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 89,54
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In den WarenkorbZustand: New.
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes Königreich
EUR 103,27
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: As New. Unread book in perfect condition.
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:. 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.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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.
Anbieter: Buchpark, Trebbin, Deutschland
EUR 54,43
Anzahl: 1 verfügbar
In den WarenkorbZustand: 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.
Anbieter: Rarewaves USA United, OSWEGO, IL, USA
EUR 132,36
Anzahl: Mehr als 20 verfügbar
In den WarenkorbHardback. 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:. 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.
HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes Königreich
EUR 92,59
Anzahl: Mehr als 20 verfügbar
In den WarenkorbHRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Sprache: Englisch
Verlag: De Gruyter, De Gruyter Sep 2014, 2014
ISBN 10: 1614515417 ISBN 13: 9781614515418
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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:- 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.
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes Königreich
EUR 107,77
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In den WarenkorbHardback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Anbieter: moluna, Greven, Deutschland
EUR 89,95
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. - Includes Text Mining and Natural Lan.
Sprache: Englisch
Verlag: De Gruyter, De Gruyter Sep 2014, 2014
ISBN 10: 1614515417 ISBN 13: 9781614515418
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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 DescriptionsWalter de Gruyter GmbH, Genthiner Strasse 13, 10785 Berlin 286 pp. Englisch.