Small airway obstruction is a main cause for chronic obstructive pulmonary disease (COPD). We propose a novel method based on machine learning to extract the airway system from a thoracic computed tomography (CT) scan. The emphasis of the proposed me...
Journal of magnetic resonance imaging : JMRI
Aug 5, 2018
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodolog...
OBJECTIVES: To train and compare machine-learning algorithms with traditional regression analysis for the prediction of early biochemical recurrence after robot-assisted prostatectomy.
Neural networks : the official journal of the International Neural Network Society
Aug 4, 2018
Representation learning algorithms are designed to learn abstract features that characterize data. State representation learning (SRL) focuses on a particular kind of representation learning where learned features are in low dimension, evolve through...
Machine computer interfaces (MCI) are assistive technologies enabling paralyzed peoples to control and communicate their environments. This study aims to discover and represents a new approach on MCI using left/right motions of voluntary jaw movement...
BACKGROUND AND PURPOSE: With extensive research efforts in place to address the clinical relevance of cerebral microbleeds (CMBs), there remains a need for fast and accurate methods to detect and quantify CMB burden. Although some computer-aided dete...
In this study, we employed a kernel support vector machine to predict epilepsy localization and lateralization for patients with a diagnosis of epilepsy (n = 228). We assessed the accuracy to which indices of verbal memory, visual memory, verbal flue...
IMPORTANCE: Current methods for identifying hospitalized patients at increased risk of delirium require nurse-administered questionnaires with moderate accuracy.
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