Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 3, 2018
Automated Gleason grading is an important preliminary step for quantitative histopathological feature extraction. Different from the traditional task of classifying small pre-selected homogeneous regions, semantic segmentation provides pixel-wise Gle...
The purpose of this study was to evaluate the performance of the deep convolutional neural network (DCNN) in differentiating between tuberculous and pyogenic spondylitis on magnetic resonance (MR) imaging, compared to the performance of three skilled...
Recent machine learning strategies for segmentation tasks have shown great ability when trained on large pixel-wise annotated image datasets. It remains a major challenge however to aggregate such datasets, as the time and monetary cost associated wi...
Traditional supervised learning classifier needs a lot of labeled samples to achieve good performance, however in many biological datasets there is only a small size of labeled samples and the remaining samples are unlabeled. Labeling these unlabeled...
This paper investigates suitability of supervised machine learning classification methods for classification of biomes using pollen datasets. We assign modern pollen samples from Africa and Arabia to five biome classes using a previously published Af...
Neural networks : the official journal of the International Neural Network Society
Aug 11, 2018
We discuss the inductive classification problem by proposing a joint framework termed Adaptive Non-negative Projective Semi-Supervised Learning (ANP-SSL). Specifically, ANP-SSL integrates the adaptive inductive label propagation, adaptive reconstruct...
UNLABELLED: Although microscopy is often treated as a quasi-static exercise for obtaining a snapshot of events and structure, it is clear that a more dynamic approach, involving real-time decision making for guiding the investigation process, may pro...
IEEE/ACM transactions on computational biology and bioinformatics
Aug 7, 2018
Although convolutional neural networks (CNN) have outperformed conventional methods in predicting the sequence specificities of protein-DNA binding in recent years, they do not take full advantage of the intrinsic weakly-supervised information of DNA...
Drug safety, also called pharmacovigilance, represents a serious health problem all over the world. Adverse drug reactions (ADRs) and drug-drug interactions (DDIs) are two important issues in pharmacovigilance, and how to detect drug safety signals h...
Biodiversity monitoring is the standard for environmental impact assessment of anthropogenic activities. Several recent studies showed that high-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) could overcome many limitations ...
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