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Proceedings Paper

Development of a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials
Author(s): Ximing Wang; Ji Hoon Park; Jeffrey Tse; Brent Liu
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Paper Abstract

Previously, we presented an ePR system to support imaging based stroke rehabilitation clinical trials. To facilitate the data analysis, we developed a generalized linear mixed effects model (GLMM) module to investigate correlation based on features extracted from textual database and imaging biomarkers. With the proposed module, the system is able to evaluate a variety of measurements including quantitative imaging features. Moreover, once an accurate GLMM model is identified from the clinical trial, the module can be used to predict outcomes for new patients based on their conditions and used as a decision support tool for optimizing the treatment plans.

Paper Details

Date Published: 25 March 2016
PDF: 10 pages
Proc. SPIE 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, 97890Y (25 March 2016); doi: 10.1117/12.2218093
Show Author Affiliations
Ximing Wang, The Univ. of Southern California (United States)
Ji Hoon Park, The Univ. of Southern California (United States)
Jeffrey Tse, The Univ. of Southern California (United States)
Brent Liu, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 9789:
Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations
Jianguo Zhang; Tessa S. Cook, Editor(s)

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