Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.
Please read the tutorial at this link: https://ebookbell.com/faq
We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.
For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.
EbookBell Team
5.0
108 reviews• 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
Focus on data extraction methods for mining biomedical literature, electronic health records, and social media including online forums, query search terms, video sharing and tweets.