Quality control (QC) is a fundamental component of any study. Diffusion MRI has unique challenges that make manual QC particularly difficult, including a greater number of artefacts than other MR modalities and a greater volume of data. The gold stan...
Drop-on-demand (DOD) printing is widely used in bioprinting for tissue engineering because of little damage to cell viability and cost-effectiveness. However, satellite droplets may be generated during printing, deviating cells from the desired posit...
MicroRNA regulation of key biological and developmental pathways is a rapidly expanding area of research, accompanied by vast amounts of experimental data. This data, however, is not widely available in bioinformatic resources, making it difficult fo...
Sequences of events have often been modeled with computational techniques, but typical preprocessing steps and problem settings do not explicitly address the ramifications of timestamped events. Clinical data, such as is found in electronic health re...
Deep learning models (aka Deep Neural Networks) have revolutionized many fields including computer vision, natural language processing, speech recognition, and is being increasingly used in clinical healthcare applications. However, few works exist w...
BACKGROUND: Esophageal schwannomas are extremely rare, with few cases reported in the literature. Traditionally, resection of esophageal schwannoma is typically performed using thoracotomy or video-assisted thoracic surgery. However, large, irregular...
PURPOSE: To develop and test the performance of a deep learning-based algorithm for glaucomatous disc identification using monoscopic fundus photographs.
IEEE journal of biomedical and health informatics
Jun 4, 2018
Spatial resolution is a critical imaging parameter in magnetic resonance imaging. The image super-resolution (SR) is an effective and cost efficient alternative technique to improve the spatial resolution of MR images. Over the past several years, th...
Random forests are a popular nonparametric tree ensemble procedure with broad applications to data analysis. While its widespread popularity stems from its prediction performance, an equally important feature is that it provides a fully nonparametric...
IEEE transactions on neural networks and learning systems
Jun 4, 2018
Inspired by the behavior of humans talking in noisy environments, we propose an embodied embedded cognition approach to improve automatic speech recognition (ASR) systems for robots in challenging environments, such as with ego noise, using binaural ...
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