We are developing MS-Analyze, a system to analyze
and detect patterns in multiple sclerosis (MS), a brain disease that
can lead to loss of motor and memory skills and even death as the
dis-ease progresses over time. Magnetic resonance imaging (MRI) is
commonly used to monitor brain changes at regular time intervals,
and MS patients are also tested for their motor and cogni-tive fitness
at similar intervals. Recent advances have resulted in MR image collection
in sev-eral different imaging modalities, each able to reveal different
aspects of MS pathology.
As different drug treatments are explored to slow or cure MS, assessments
of their effectiveness will require consideration of all the various
data that are monitored. The most reliable correlation of changes
in pathology following drug treatments with the treatments themselves
will require access to large amounts of integrated data, which is
usually not available to any one given labo-ratory.
MS-Analyze addresses both the challenges of amassing and analyzing
data by combining data collection, data fusion, data analysis, and
secure data sharing in one system. Our ongoing system development
is motivated by a desire to generate new methods for representing
and managing heterogeneous data streams. In addition to any immediate
benefits in the treatment of MS, we hope it will provide new tools
for data sharing and research collaboration, algorithms for fast pat-tern
discovery, and an evaluation environment for studying the issues involved
in sharing sensi-tive information. |
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