Exploiting the rich information found in electronic health
records (EHRs) can facilitate better medical research and improve
the quality of medical practice. Until now, a trivial amount of
research has been published on the challenges of leveraging this
information. Addressing these challenges, Information Discovery on
Electronic Health Records explores the technology to unleash the
data stored in EHRs.
Assembling a truly interdisciplinary team of experts, the book
tackles medical privacy concerns, the lack of standardization for
the representation of EHRs, missing or incorrect values, and the
availability of multiple rich health ontologies. It looks at how to
search the EHR collection given a user query and return relevant
fragments from the EHRs. It also explains how to mine the EHR
collection to extract interesting patterns, group entities to
various classes, or decide whether an EHR satisfies a given
property. Most of the book focuses on textual or numeric data of
EHRs, where more searching and mining progress has occurred. A
chapter on the processing of medical images is also included.
Maintaining a uniform style across chapters and minimizing
technical jargon, this book presents the various ways to extract
useful knowledge from EHRs. It skillfully discusses how EHR data
can be effectively searched and mined.
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