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* 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
This book constitutes the refereed proceedings of the 35th Annual
IFIP WG 11.3 Conference on Data and Applications Security and
Privacy, DBSec 2021, held in Calgary, Canada, in July 2021.*The 15
full papers and 8 short papers presented were carefully reviewed
and selected from 45 submissions. The papers present high-quality
original research from academia, industry, and government on
theoretical and practical aspects of information security. They are
organized in topical sections named differential privacy,
cryptology, machine learning, access control and others. *The
conference was held virtually due to the COVID-19 pandemic.
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