OBJECTIVES: The FUTUREPAIN study develops a short general-purpose questionnaire, based on the biopsychosocial model, to predict the probability of developing or maintaining moderate-to-severe chronic pain 7-10 years into the future.
From its origins in epidemiology, evidence-based medicine has promulgated a rigorous approach to assessing the validity, impact and applicability of hypothesis-driven empirical research used to evaluate the utility of diagnostic tests, prognostic too...
In this position paper, we provide a collection of views on the role of AI in the COVID-19 pandemic, from clinical requirements to the design of AI-based systems, to the translation of the developed tools to the clinic. We highlight key factors in de...
Neural networks : the official journal of the International Neural Network Society
Aug 19, 2020
Convolutional neural networks (CNNs) are widely used to recognize the user's state through electroencephalography (EEG) signals. In the previous studies, the EEG signals are usually fed into the CNNs in the form of high-dimensional raw data. However,...
Journal of chemical information and modeling
Aug 19, 2020
Deep learning has demonstrated significant potential in advancing state of the art in many problem domains, especially those benefiting from automated feature extraction. Yet, the methodology has seen limited adoption in the field of ligand-based vir...
To achieve the satisfactory performance of human action recognition, a central task is to address the sub-action sharing problem, especially in similar action classes. Nevertheless, most existing convolutional neural network (CNN)-based action recogn...
Fully convolutional neural network (FCN) has achieved great success in semantic segmentation. However, the performance of the FCN is generally compromised for multi-object segmentation. Multi-organ segmentation is very common while challenging in the...
INTRODUCTION: Electrode misplacement and interchange errors are known problems when recording the 12‑lead electrocardiogram (ECG). Automatic detection of these errors could play an important role for improving clinical decision making and outcomes in...
In this research, an efficient scheme to identify leaf types is proposed. In that scheme, the leaf boundary points are fitted in a continuous contour using Radial Basis Function Neural Networks (RBFNN) to calculate the centroid of the leaf shape. Aft...
BACKGROUND: As the population ages, the incidence of traumatic falls has been increasing. We hypothesize that a machine learning algorithm can more accurately predict mortality after a fall compared with a standard logistic regression (LR) model base...
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