NCBO Webinar: Yehoshua Perl on Sep. 12 at 10am PT

The next NCBO Webinar will be presented TOMORROW by Dr. Yehoshua Perl from
the New Jersey Institute of Technology on "Abstraction networks to support
comprehension and auditing for terminologies" at 10:00am PT, Wednesday,
Sep. 12. Below is information on how to join the online meeting via WebEx
and accompanying teleconference.

ABSTRACT:
Biomedical terminologies are large and complex and by their nature are
error-prone. Hence, Quality Assurance (QA)  or auditing should be an
inherent part of the  terminology life cycle. The importance of QA is
increasing  with the spread of terminology-use in Biomedical research and
in  the health care industry. Terminology QA is  especially critical  with
the current ARRA initiative of enhancing the meaningful  use of EMRs in
health care.  Terminology domain expert editors who can perform QA work
require multidisciplinary training and are a scarce resource. This fact
combined with budget constraints for terminology maintenance are ruling out
manual auditing of a complete terminology as impractical. However, the
value of using terminologies in the Biomedical industry depends on the
correctness and accuracy of their implemented knowledge.

To overcome this shortage in trained terminology experts, there is a need
to automate part of the terminology QA work. However, most terminology
errors require an expert editor's review. One approach to solve this
problem is to develop automatic computational  techniques for identifying
concepts and relationships with high probability of errors. Directing
editors' efforts toward reviewing such concepts and relationships will
increase their QA productivity. Abstraction networks for terminologies were
proven to support such automatic computational techniques.

Abstraction networks are compact "semantic" networks, which summarize the
knowledge in a much larger terminology. They provide orientation to the
content and structure of a terminology, urgently needed by editors and
users alike.  In this presentation we will explore various kinds of
abstraction networks and their properties. Some properties of abstraction
networks will be shown to provide improved orientation and QA support. We
will demonstrate how abstraction networks help in identifying groups of
concepts with high likelihood of errors.  Examples of abstraction networks
for UMLS, SNOMED, NCIt and the Columbia MED will be presented and used to
illustrate their support for terminology QA work.


SPEAKER BIO:
Dr. Perl received his PhD in Computer Science from the Weizmann Institute
of Science in Israel in 1975. He is currently a Professor of Computer
Science at the New Jersey Institute of Technology (NJIT). He has published
over 80 journal paper and 60 conference papers in top Computer Science and
Medical Informatics journals and conferences.  Dr. Perl has been working in
the field of “medical terminologies” for the last 18 years, following his
earlier research career in the theory of algorithms. Dr. Perl was awarded
the Harlan Perlis NJIT Research Award in 1996 for his earlier research, and
the NJIT College of Computing Sciences Excellence in Research Award in 2008
for his research in Biomedical Terminologies.

The NJIT Terminology Research Group, upgraded in 2007 to the Structural
Analysis of Biomedical Ontologies Center (SABOC), has established a strong
research record in the design of structural techniques for partitioning,
abstraction and quality assurance of medical terminologies such as the
Columbia MED, the UMLS, the NCIt and SNOMED.  Many publications in top
Medical Informatics journals and conferences have validated Dr. Perl's and
the SABOC Center's major research theme, namely that structural analysis of
terminologies can automatically pinpoint areas of high likelihood of
inconsistencies, errors and necessary enhancements.


WEBEX DETAILS:
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To start or join the online meeting
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Go to
https://stanford.webex.com/stanford/j.php?ED=203714637&UID=481527042&PW=NYzJjN2E4MzEy&RT=MiM0
Meeting Number: 921 649 715
Meeting Password: ncbo

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Audio conference information
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meeting, or call the number below and enter the access code.
Call-in toll number (US/Canada): 1-650-429-3300
Global call-in numbers:
https://stanford.webex.com/stanford/globalcallin.php?serviceType=MC&ED=203714637&tollFree=0

Access code:921 649 715