AIMC Topic: Semantics
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Architecture and usability of OntoKeeper, an ontology evaluation tool.
BMC medical informatics and decision making
Aug 8, 2019
BACKGROUND: The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automated tools may help to ease th...
Detection of medical text semantic similarity based on convolutional neural network.
BMC medical informatics and decision making
Aug 7, 2019
BACKGROUND: Imaging examinations, such as ultrasonography, magnetic resonance imaging and computed tomography scans, play key roles in healthcare settings. To assess and improve the quality of imaging diagnosis, we need to manually find and compare t...
A Neural Network-Inspired Approach for Improved and True Movie Recommendations.
Computational intelligence and neuroscience
Aug 4, 2019
In the last decade, sentiment analysis, opinion mining, and subjectivity of microblogs in social media have attracted a great deal of attention of researchers. Movie recommendation systems are the tools, which provide valuable services to the users. ...
TGV Upsampling: A Making-Up Operation for Semantic Segmentation.
Computational intelligence and neuroscience
Aug 1, 2019
With the widespread use of deep learning methods, semantic segmentation has achieved great improvements in recent years. However, many researchers have pointed out that with multiple uses of convolution and pooling operations, great information loss ...
A disease inference method based on symptom extraction and bidirectional Long Short Term Memory networks.
Methods (San Diego, Calif.)
Jul 10, 2019
The wide applications of automatic disease inference in many medical fields improve the efficiency of medical treatments. Many efforts have been made to predict patients' future health conditions according to their full clinical texts, clinical measu...
Unsupervised word embeddings capture latent knowledge from materials science literature.
Nature
Jul 3, 2019
The overwhelming majority of scientific knowledge is published as text, which is difficult to analyse by either traditional statistical analysis or modern machine learning methods. By contrast, the main source of machine-interpretable data for the ma...
Neural Multimodal Cooperative Learning Toward Micro-Video Understanding.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Jul 1, 2019
The prevailing characteristics of micro-videos result in the less descriptive power of each modality. The micro-video representations, several pioneer efforts proposed, are limited in implicitly exploring the consistency between different modality in...
HPO2Vec+: Leveraging heterogeneous knowledge resources to enrich node embeddings for the Human Phenotype Ontology.
Journal of biomedical informatics
Jun 27, 2019
BACKGROUND: In precision medicine, deep phenotyping is defined as the precise and comprehensive analysis of phenotypic abnormalities, aiming to acquire a better understanding of the natural history of a disease and its genotype-phenotype associations...
Adaptive Learning Emotion Identification Method of Short Texts for Online Medical Knowledge Sharing Community.
Computational intelligence and neuroscience
Jun 25, 2019
The medical knowledge sharing community provides users with an open platform for accessing medical resources and sharing medical knowledge, treatment experience, and emotions. Compared with the recipients of general commodities, the recipients in the...
Distant supervision for treatment relation extraction by leveraging MeSH subheadings.
Artificial intelligence in medicine
Jun 7, 2019
The growing body of knowledge in biomedicine is too vast for human consumption. Hence there is a need for automated systems able to navigate and distill the emerging wealth of information. One fundamental task to that end is relation extraction, wher...
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