We built a natural language processing (NLP) method to automatically extract clinical findings in radiology reports and characterize their level of change and significance according to a radiology-specific information model. We utilized a combination...
Objective Recent studies have investigated the role of spinal image guidance for pedicle screw placement. Many authors have observed an elevated placement accuracy and overall improvement of outcome measures. This study assessed a bi-institutional ex...
The study aimed to determine if computer vision techniques rooted in deep learning can use a small set of radiographs to perform clinically relevant image classification with high fidelity. One thousand eight hundred eighty-five chest radiographs on ...
Journal of X-ray science and technology
Jan 1, 2017
BACKGROUND: Non-intrusive inspection systems based on X-ray radiography techniques are routinely used at transport hubs to ensure the conformity of cargo content with the supplied shipping manifest. As trade volumes increase and regulations become mo...
A 5-y-old female ferret (Mustela putorius furo) was evaluated for diarrhea, anorexia, and lethargy for 1 wk. Only mild dehydration was detected on physical examination. CBC analysis revealed marked erythrocytosis with an unremarkable plasma biochemis...
Among various surgical methods introduced to optimize esthetic results, robotic surgery has gradually expanded in scope. As incision, approach, and operation view in robotic surgery differ from existing surgical methods, we should consider reconstruc...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jan 1, 2015
Dementia, Alzheimer's disease (AD) in particular is a global problem and big threat to the aging population. An image based computer-aided dementia diagnosis method is needed to providing doctors help during medical image examination. Many machine le...
OBJECTIVE: The purpose of the proposed study was to develop an identification unit for classifying periodontal diseases using support vector machine (SVM), decision tree (DT), and artificial neural networks (ANNs).
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