Mild traumatic brain injury (mTBI) patients account for more than 70% of all TBI, with a subset experiencing persistent post concussive symptoms more than 3 months post injury. Patients clinical presentation and conventional imaging findings acutely post injury often lack the ability to predict chronic outcome. In this study, we present a novel method for latent feature extraction from volumetric MRI. We show that with machine learning methods, these acute latent volumetric MRI features are able to improve our symptom prediction in mTBI patients at 18 months post injury.
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