Computational Intelligence - May 2013 - 15

Conference
Report

Gary B. Fogel
Natural Selection, Inc.,
USA

A Report on the IEEE Life Sciences Grand Challenges Conference

o

n October 4-5, 2012 I had the
good fortune to attend the first
IEEE Life Sciences Grand Challenges Conference (IEEE LSGCC) held
at the National Academy of Sciences in
Washington, D.C. The two day meeting
had attendees from essentially all IEEE
societies, reviewing applications and
advancements of engineering in biomedicine. IEEE Life Sciences represents
a new direction for IEEE, focused on the
ever increasing need for improved engineering solutions for high quality, lower
cost solutions to healthcare. As biology
generates larger datasets, the need for
computational intelligence approaches
also increases. As a biologist, it was excellent to see presentations from both engineers and biologists, with IEEE pulling
the two fields closer together.
The meeting itself was largely
focused on medical applications, including improved devices, use of robots as
medical assistants, even visualization
methods for modeling of biological systems such as blood flow in the heart so
that new types of replacement valves
could be tested in a realistic simulation
environment where the researcher can
interact with the simulation in three
dimensional projections.
IEEE CIS was mentioned in a lecture by Shangkai Gao (Tsinghua University) regarding the importance of and
future directions in brain-computer
interfaces. It was good to see the importance of machine learning featured, as
Digital Object Identifier 10.1109/MCI.2013.2247821
Date of publication: 11 April 2013

The start of the first IEEE Life Sciences Grand Challenges Conference in Washington, D.C. at the
National Academy of Sciences.

well as a cover from a previous special
issue on this topic in IEEE Computational Intelligence Magazine!
A highlight for me was the lecture
by Nobel Prize winner Phillip Sharp
on the convergence of the life sciences, physical sciences, and engineering. It is this convergence that was the
focus of the meeting, the will allow
for knowledge integration and iteration, to provide actionable insights to
future clinicians. A common theme in
many talks was the need to translate
better modeling and engineer ing
throughout the healthcare chain, not
just to the clinician but to better

informed and engaged patients. While
some presentations highlighted promising advances already being made in
these directions, the advent of big data
in biology and the realization of the
scope and size of the problems in systems biology remain daunting. These
"grand challenges" will be the reason
why this new direction for IEEE will
pay dividends for researchers and
patients for years to come.
For more information on the IEEE
Life Sciences Initiative, please visit
http://lifesciences.ieee.org.

MAY 2013 | IEEE CoMputAtIonAl IntEllIgEnCE MAgAzInE

15



http://lifesciences.ieee.org

Table of Contents for the Digital Edition of Computational Intelligence - May 2013

Computational Intelligence - May 2013 - Cover1
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Computational Intelligence - May 2013 - 1
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