[CSEE Talk] [Csee-faculty-tt] talk: multi-scale approach to analyze large clinical datasets, 1pm Fri 4/11 ITE325b

[Tim Oates]

This talk is at NOON on THURSDAY of this week, April 10th.  Please do plan
on attending!

   - tim

On Mon, 7 Apr 2014, Tim Finin wrote:

> 	      Computer Science and Electrical Engineering
> 	        University of Maryland, Baltimore County
>
>       A multi-scale approach to analyze large clinical datasets:
>    Towards the understanding of the complex effects of concussions
>
> 		 	   Dr. Jesus Caban
> 		 National Intrepid Center of Excellence
> 			      Walter Reed
>
> 		1:00pm Friday, 11 April 2014, ITE325b
>
> Mild traumatic brain injuries (mTBIs) or concussions are invisible
> injuries that are poorly understood and their sequelae can be
> difficult to diagnose.  Individuals who have had concussions are at an
> increased risk of depression, post-traumatic stress disorder (PTSD),
> headaches, concentration difficulties, and other problems.  During the
> last decade, a significant amount of attention has been given to the
> acquisition of clinical data from patients suffering from mTBI.
> Unfortunately, most of the data collection and analysis have focused
> on individual aspects of the injury, not necessarily on comprehensive
> and multi-modal analytical techniques to capture the complex
> biological state of mTBI patients.
>
> This talk will discuss a large-scale informatics database that has
> been developed to enable interdisciplinary research on mTBI and will
> introduce a multi-scale approach to mine complex clinical datasets.
> The millions of multi-modal elements originated from different
> clinical disciplines are treated as weak features and modeled
> independently to generate stronger features.  Three cases of going
> from weak to stronger features will be discussed including (a) an
> inductive/transductive model to extract stable image features from
> multi-modal MRI scans, (b) a rule-based model used to infer knowledge
> from blood measurements, and (c) a sentiment analysis-based model to
> extract behavioral signals from writing samples.  Once stronger
> features are obtained, a relational model is used to integrate the
> data and extract new knowledge from such a complex dataset.
>
>
> Dr. Caban is the Acting Chief of Clinical & Research Informatics at
> the National Intrepid Center of Excellence (NICoE) at Walter Reed
> Bethesda.  He received a Ph.D. in Computer Science from UMBC (2009),
> his M.S. degree in Computer Science from the University of Kentucky
> (2005), and his B.S. in Computer Science from the University of Puerto
> Rico (2002).  Over the last eight years Dr. Caban's research has
> focused on the design and development of techniques to analyze
> clinical and imaging data.  His research and experience has given him
> the opportunity to work at top research and healthcare organizations
> including the National Institutes of Health, John Hopkins
> University, the University of Maryland Medical Center, and IBM
> Research.  Dr. Caban is presently an adjunct faculty member at John
> Hopkins University Applied Physics Lab and a part-time instructor at
> the Department of Computer Science at UMBC.  Recently, he received the
> 2013-14 JHU/APL Junior faculty award for his commitment to teaching.
> Currently, he is serving as the Associate Editor of the JAMIA special
> issue on Visual Analytics in Healthcare and as the contracting officer
> representative for the DoD program on "Watson-Like Technologies for
> TBI/PTSD Clinical Decision Support and Predictive Analytics".
>
> Host: Tim Oates (oates at umbc.edu)
>
>    -- more information and directions: http://bit.ly/UMBCtalks --
> --
> For info and options, see 
> http://lists.cs.umbc.edu/mailman/listinfo/csee-colloquium-out
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>

---------------------------------------
Tim Oates, Professor
Department of CS and EE
University of Maryland Baltimore County
(410) 455-3082
http://www.cs.umbc.edu/~oates