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Context-Aware Feature Query to Improve the Prediction Performancer: The decision to select which features to use andquery can be effectively addressed based on the available featuresor context. This paper presents a novel approach based on de-noising autoencoders and sensitivity analysis in neural networksto efficiently query for unknown features given the context.
An Active Learning Based Prediction of Epidural Stimulation Outcome in Spinal Cord Injury Patients Using Dynamic Sample weighting: Recent studies suggest that epidural stimulation of the spinal cord could increase the motor pattern both in motor and sensory complete spinal cord injury (SCI) patients. This paper presents a novel technique using machine learning methods to predict the functionality of a SCI patient after epidural stimulation.
Feasibility of a Secure Wireless Sensing Smartwatch Application for the Self-Management of Pediatric Asthma: To address the need for asthma self-management in pediatrics, we present the feasibility of a mobile health (mHealth) platform built on their prior work in an asthmatic adult and child.
Remote and Personalized Systems for Clinical Outcomes Research
Professor, Texas A&M University
Assessment of Movement Disorders in Patients with Degenerative Spinal Cord Disorders
Professor, Massachusetts Amherst