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Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Volume 7, 2019 - Issue 3: Special Issue: 2nd and 3rd MICCAI workshop on Deep Learning in Medical Image Analysis
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Original Articles

Deep learning of brain lesion patterns and user-defined clinical and MRI features for predicting conversion to multiple sclerosis from clinically isolated syndrome

Youngjin YooDepartment of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada.;Biomedical Engineering Program, University of British Columbia, Vancouver, Canada.;MS/MRI Research Group, University of British Columbia, Vancouver, Canada.Correspondence[email protected]
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Lisa Y. W. TangDepartment of Radiology, University of British Columbia, Vancouver, Canada.;MS/MRI Research Group, University of British Columbia, Vancouver, Canada.View further author information
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David K. B. LiDepartment of Radiology, University of British Columbia, Vancouver, Canada.;MS/MRI Research Group, University of British Columbia, Vancouver, Canada.View further author information
,
Luanne MetzDivision of Neurology, University of Calgary, Calgary, Canada.View further author information
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Shannon KolindDivision of Neurology, University of British Columbia, Vancouver, Canada.View further author information
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Anthony L. TraboulseeDivision of Neurology, University of British Columbia, Vancouver, Canada.;MS/MRI Research Group, University of British Columbia, Vancouver, Canada.View further author information
&
Roger C. TamBiomedical Engineering Program, University of British Columbia, Vancouver, Canada.;Department of Radiology, University of British Columbia, Vancouver, Canada.;MS/MRI Research Group, University of British Columbia, Vancouver, Canada.View further author information
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Pages 250-259 | Received 31 Jan 2017, Accepted 11 Jul 2017, Published online: 09 Aug 2017

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