Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verifi...
Computational and mathematical methods in medicine
Sep 28, 2015
In order to build a reliable index to monitor the depth of anesthesia (DOA), many algorithms have been proposed in recent years, one of which is sample entropy (SampEn), a commonly used and important tool to measure the regularity of data series. How...
Geriatrics & gerontology international
Sep 3, 2015
AIM: We investigated the prognostic value of preoperative N-terminal pro-brain natriuretic peptide (NT-proBNP) in non-cardiac surgery in elderly patients who showed normal left ventricular function on preoperative echocardiography.
Neural networks : the official journal of the International Neural Network Society
Aug 4, 2015
In this paper, we investigate the problem of optimization of multivariate performance measures, and propose a novel algorithm for it. Different from traditional machine learning methods which optimize simple loss functions to learn prediction functio...
OBJECTIVES: To determine gene-gene interactions and missing heritability of complex diseases is a challenging topic in genome-wide association studies. The multifactor dimensionality reduction (MDR) method is one of the most commonly used methods for...
Progress in neuro-psychopharmacology & biological psychiatry
Jul 4, 2015
BACKGROUND: Resting-state functional magnetic resonance imaging studies examining low frequency fluctuations (0.01-0.08 Hz) have revealed atypical whole brain functional connectivity patterns in adolescents with autism spectrum disorder (ASD), and th...
Machine learning based classification algorithms like support vector machines (SVMs) have shown great promise for turning a high dimensional neuroimaging data into clinically useful decision criteria. However, tracing imaging based patterns that cont...
OBJECTIVE: The purpose of this study is to evaluate the ability of machine learning to discriminate between magnetic resonance images (MRI) of normal and pathological human articular cartilage obtained under standard clinical conditions.
OBJECTIVE: Ruptured abdominal aortic aneurysm (rAAA) carries a high mortality rate, even with prompt transfer to a medical center. An artificial neural network (ANN) is a computational model that improves predictive ability through pattern recognitio...
BACKGROUND: Pediatric traumatic brain injury (TBI) constitutes a significant burden and diagnostic challenge in the emergency department (ED). While large North American research networks have derived clinical prediction rules for the head injured ch...