Overview
- Describes a recommender system for tinnitus to help physicians diagnose and treat tinnitus patients
- Presents an introduction to the topic of tinnitus
- Highlights the basic concepts of recommender systems (RS), the current state-of-the-art and their real-world applications in different areas
- Focuses on health recommender systems
- Proposes a knowledge discovery approach to developing decision support systems
- Presents theoretical concepts and algorithms for rule-based systems, including: decision tables, classification rules, action rule extraction, and meta-actions
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 685)
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Table of contents (11 chapters)
Keywords
About this book
It describes experiments on extracting novel knowledge from the historical dataset of patients treated by Dr. P. Jastreboff so that to better understand factors behind therapy's effectiveness and better personalize treatments for different profiles of patients.
The book is a response for a growing demand of an advanced data analytics in the healthcare industry in order to provide better care with the data driven decision-making solutions.
The potential economic benefits of applying computerized clinical decision support systems include not only improved efficiency in health care delivery (by reducing costs, improving quality of care and patient safety), but also enhancement in treatment's standardization, objectivity and availability in places of scarce expert's knowledge on this difficult to treat hearing disorder.
Furthermore, described approach could be used in assessment of the clinical effectiveness of evidence-based intervention of various proposed treatments for tinnitus.
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Bibliographic Information
Book Title: Decision Support System for Diagnosis and Treatment of Hearing Disorders
Book Subtitle: The Case of Tinnitus
Authors: Katarzyna A. Tarnowska, Zbigniew W. Ras, Pawel J. Jastreboff
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-51463-5
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-51462-8Published: 03 March 2017
Softcover ISBN: 978-3-319-84657-6Published: 21 July 2018
eBook ISBN: 978-3-319-51463-5Published: 24 February 2017
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 160
Number of Illustrations: 33 b/w illustrations
Topics: Computational Intelligence, Artificial Intelligence, Health Informatics