In this paper we probe the interaction between sequential and hierarchical learning by investigating implicit learning in a group of school-aged children. We administered a serial reaction time task, in the form of a modified Simon Task in which the ...
International journal of medical informatics
May 13, 2020
BACKGROUND: Many studies that aim to identify gene biomarkers using statistical methods and translate them into FDA-approved drugs have faced challenges due to lack of clinical validity and methodological reproducibility. Since genomic data analysis ...
Neural networks : the official journal of the International Neural Network Society
May 13, 2020
Accurately segmenting contrast-filled vessels from X-ray coronary angiography (XCA) image sequence is an essential step for the diagnosis and therapy of coronary artery disease. However, developing automatic vessel segmentation is particularly challe...
The recognition of activities of daily living (ADL) in smart environments is a well-known and an important research area, which presents the real-time state of humans in pervasive computing. The process of recognizing human activities generally invol...
ChIP-seq is one of the core experimental resources available to understand genome-wide epigenetic interactions and identify the functional elements associated with diseases. The analysis of ChIP-seq data is important but poses a difficult computation...
Journal of neuroengineering and rehabilitation
May 13, 2020
BACKGROUND: Human-likeliness of robot movements is a key component to enable a safe and effective human-robot interaction, since it contributes to increase acceptance and motion predictability of robots that have to closely interact with people, e.g....
Robot-assisted cardiovascular surgery is used to avoid surgeon suffering from X-ray radiation and relieve fatigue caused by long-time standing wearing protective clothing. Its remote surgery can alleviate the lack of experienced doctors in remote are...
Deep convolutional neural networks (DCNNs) show impressive similarities to the human visual system. Recent research, however, suggests that DCNNs have limitations in recognizing objects by their shape. We tested the hypothesis that DCNNs are sensitiv...
BACKGROUND: Screening for chronic kidney disease is a challenge in community and primary care settings, even in high-income countries. We developed an artificial intelligence deep learning algorithm (DLA) to detect chronic kidney disease from retinal...
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