Overview
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Electrical and Computer Engineering (BRIEFSELECTRIC)
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Table of contents (6 chapters)
Keywords
About this book
Anonymization of Electronic Medical Records to Support Clinical Analysis closely examines the privacy threats that may arise from medical data sharing, and surveys the state-of-the-art methods developed to safeguard data against these threats.
To motivate the need for computational methods, the book first explores the main challenges facing the privacy-protection of medical data using the existing policies, practices and regulations. Then, it takes an in-depth look at the popular computational privacy-preserving methods that have been developed for demographic, clinical and genomic data sharing, and closely analyzes the privacy principles behind these methods, as well as the optimization and algorithmic strategies that they employ. Finally, through a series of in-depth case studies that highlight data from the US Census as well as the Vanderbilt University Medical Center, the book outlines a new, innovative class of privacy-preserving methods designed to ensure the integrityof transferred medical data for subsequent analysis, such as discovering or validating associations between clinical and genomic information.
Anonymization of Electronic Medical Records to Support Clinical Analysis is intended for professionals as a reference guide for safeguarding the privacy and data integrity of sensitive medical records. Academics and other research scientists will also find the book invaluable.
Authors and Affiliations
Bibliographic Information
Book Title: Anonymization of Electronic Medical Records to Support Clinical Analysis
Authors: Aris Gkoulalas-Divanis, Grigorios Loukides
Series Title: SpringerBriefs in Electrical and Computer Engineering
DOI: https://doi.org/10.1007/978-1-4614-5668-1
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: The Author(s) 2013
Softcover ISBN: 978-1-4614-5667-4Published: 13 October 2012
eBook ISBN: 978-1-4614-5668-1Published: 13 October 2012
Series ISSN: 2191-8112
Series E-ISSN: 2191-8120
Edition Number: 1
Number of Pages: XV, 72
Number of Illustrations: 23 b/w illustrations
Topics: Health Informatics, Data Mining and Knowledge Discovery, Information Storage and Retrieval
Industry Sectors: Biotechnology, Health & Hospitals, IT & Software, Pharma