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Activity Number:
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224
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2009 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #304303 |
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Title:
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Spatio-Temporal Modeling of Electrical Muscle Resistance of Patients with Amyotrophic Lateral Sclerosis Using Generalized Additive Mixed Model
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Author(s):
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Catherine Stamoulis*+ and Seward Rutkove
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Companies:
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Harvard Medical School and Harvard Medical School
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Address:
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Beth Israel Deaconess Medical Center, Boston, MA, 02215,
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Keywords:
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Amyotrophic Lateral Sclerosis ; Generalized Additive Mixed Models ; Longitudinal data
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Abstract:
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Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive muscle paralysis. The frequency spectrum of muscle electrical resistance varies temporally and spatially, when longitudinal measurements are made at distinct locations on the muscle. These variations are correlated and may not be modeled accurately using mixed models with separate temporal and spatial terms. Generalized additive mixed models (GAMMs) provide a better framework for the functional dependence of muscle resistance on time and space. For a set of 18 ALS patients we developed a GAMM model and estimated two-dimensional functions of time and space using smoothing splines, and smoothing parameters using penalized likelihood. Based on model selection criteria, the GAMM model fitted the data significantly better than a linear mixed model with separate temporal and spatial terms.
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