AI Medical Compendium Topic:
Semantics

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Bio-semantic relation extraction with attention-based external knowledge reinforcement.

BMC bioinformatics
BACKGROUND: Semantic resources such as knowledge bases contains high-quality-structured knowledge and therefore require significant effort from domain experts. Using the resources to reinforce the information retrieval from the unstructured text may ...

SemanticGO: a tool for gene functional similarity analysis in Arabidopsis thaliana and rice.

Plant science : an international journal of experimental plant biology
Gene or pathway functional similarities are important information for researchers. However, these similarities are often described sparsely and qualitatively. The latent semantic analysis of Arabidopsis thaliana (Arabidopsis) Gene Ontology (GO) data ...

Extracting drug-drug interactions from texts with BioBERT and multiple entity-aware attentions.

Journal of biomedical informatics
Drug-drug interactions (DDIs) extraction is one of the important tasks in the field of biomedical relation extraction, which plays an important role in the field of pharmacovigilance. Previous neural network based models have achieved good performanc...

Encoder-decoder CNN models for automatic tracking of tongue contours in real-time ultrasound data.

Methods (San Diego, Calif.)
One application of medical ultrasound imaging is to visualize and characterize human tongue shape and motion in real-time to study healthy or impaired speech production. Due to the low-contrast characteristic and noisy nature of ultrasound images, it...

Uni-image: Universal image construction for robust neural model.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks have shown high performance in prediction, but they are defenseless when they predict on adversarial examples which are generated by adversarial attack techniques. In image classification, those attack techniques usually perturb ...

Chinese Emergency Event Recognition Using Conv-RDBiGRU Model.

Computational intelligence and neuroscience
In view of the weak generalization of traditional event recognition methods, the limitation of dependence on field knowledge of expert, the longer train time of deep neural network, and the problem of gradient dispersion, the neural network joint mod...

Detecting modeling inconsistencies in SNOMED CT using a machine learning technique.

Methods (San Diego, Calif.)
SNOMED CT is a comprehensive and evolving clinical reference terminology that has been widely adopted as a common vocabulary to promote interoperability between Electronic Health Records. Owing to its importance in healthcare, quality assurance becom...

Summarization of biomedical articles using domain-specific word embeddings and graph ranking.

Journal of biomedical informatics
Text summarization tools can help biomedical researchers and clinicians reduce the time and effort needed for acquiring important information from numerous documents. It has been shown that the input text can be modeled as a graph, and important sent...

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study.

The Lancet. Digital health
BACKGROUND: CT is the most common imaging modality in traumatic brain injury (TBI). However, its conventional use requires expert clinical interpretation and does not provide detailed quantitative outputs, which may have prognostic importance. We aim...