Interdisciplinary sciences, computational life sciences
Mar 17, 2021
Discovering relations of cross-type biomedical entities is crucial for biology research. A large amount of potential or indirect connected biological relations is hidden in millions of biomedical literatures and biological databases. The previous rul...
New technologies with unprecedented agentic capabilities (i.e., action selection, protocol development) are now introduced in organizations such as Big Data, 3D printing or artificial intelligence. Because they are endowed with novel capabilities tha...
Journal of evaluation in clinical practice
Feb 11, 2021
RATIONALE, AIMS AND OBJECTIVES: The diversity of types of evidence (eg, case reports, animal studies and observational studies) makes the assessment of a drug's safety profile into a formidable challenge. While frequentist uncertain inference struggl...
BACKGROUND: Despite the benefits offered by an abundance of health applications promoted on app marketplaces (e.g., Google Play Store), the wide adoption of mobile health and e-health apps is yet to come.
IEEE transactions on neural networks and learning systems
Jan 4, 2021
Convolutional neural networks (CNNs) have shown an effective way to learn spatiotemporal representation for action recognition in videos. However, most traditional action recognition algorithms do not employ the attention mechanism to focus on essent...
IEEE transactions on neural networks and learning systems
Jan 4, 2021
Deep convolutional neural networks have been widely used in numerous applications, but their demanding storage and computational resource requirements prevent their applications on mobile devices. Knowledge distillation aims to optimize a portable st...
BACKGROUND: Entity normalization is an important information extraction task which has gained renewed attention in the last decade, particularly in the biomedical and life science domains. In these domains, and more generally in all specialized domai...
Neural networks : the official journal of the International Neural Network Society
Dec 5, 2020
Knowledge graph reasoning aims to find reasoning paths for relations over incomplete knowledge graphs (KG). Prior works may not take into account that the rewards for each position (vertex in the graph) may be different. We propose the distance-aware...
IEEE journal of biomedical and health informatics
Dec 4, 2020
Image classification using convolutional neural networks (CNNs) outperforms other state-of-the-art methods. Moreover, attention can be visualized as a heatmap to improve the explainability of results of a CNN. We designed a framework that can generat...
Neural networks : the official journal of the International Neural Network Society
Nov 21, 2020
Relation Extraction systems train an extractor by aligning relation instances in Knowledge Base with a large amount of labeled corpora. Since the labeled datasets are very expensive, Distant Supervision Relation Extraction (DSRE) utilizes rough corpu...
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