AIMC Topic: Semantics
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Measuring the effect of different types of unsupervised word representations on Medical Named Entity Recognition.
International journal of medical informatics
Jun 5, 2019
BACKGROUND: This work deals with Natural Language Processing applied to the clinical domain. Specifically, the work deals with a Medical Entity Recognition (MER) on Electronic Health Records (EHRs). Developing a MER system entailed heavy data preproc...
Contextual label sensitive gated network for biomedical event trigger extraction.
Journal of biomedical informatics
Jun 5, 2019
Biomedical events play a key role in improving biomedical research. Event trigger identification, extracting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. There exist ...
Ontology mapping for semantically enabled applications.
Drug discovery today
May 31, 2019
In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an increasing amount and variety of data. This is particularly important for realising the full potential...
Supervised methods to extract clinical events from cardiology reports in Italian.
Journal of biomedical informatics
May 28, 2019
Clinical narratives are a valuable source of information for both patient care and biomedical research. Given the unstructured nature of medical reports, specific automatic techniques are required to extract relevant entities from such texts. In the ...
Adaptive Feature Recombination and Recalibration for Semantic Segmentation With Fully Convolutional Networks.
IEEE transactions on medical imaging
May 20, 2019
Fully convolutional networks have been achieving remarkable results in image semantic segmentation, while being efficient. Such efficiency results from the capability of segmenting several voxels in a single forward pass. So, there is a direct spatia...
Semantic Face Hallucination: Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes.
IEEE transactions on pattern analysis and machine intelligence
May 14, 2019
Given a tiny face image, existing face hallucination methods aim at super-resolving its high-resolution (HR) counterpart by learning a mapping from an exemplary dataset. Since a low-resolution (LR) input patch may correspond to many HR candidate patc...
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding.
IEEE transactions on pattern analysis and machine intelligence
May 14, 2019
Research on depth-based human activity analysis achieved outstanding performance and demonstrated the effectiveness of 3D representation for action recognition. The existing depth-based and RGB+D-based action recognition benchmarks have a number of l...
Smoothing dense spaces for improved relation extraction between drugs and adverse reactions.
International journal of medical informatics
May 13, 2019
BACKGROUND AND OBJECTIVE: This work aims at extracting Adverse Drug Reactions (ADRs), i.e. a harm directly caused by a drug at normal doses, from Electronic Health Records (EHRs). The lack of readily available EHRs because of confidentiality issues a...
A mobile health monitoring-and-treatment system based on integration of the SSN sensor ontology and the HL7 FHIR standard.
BMC medical informatics and decision making
May 10, 2019
BACKGROUND: Mobile health (MH) technologies including clinical decision support systems (CDSS) provide an efficient method for patient monitoring and treatment. A mobile CDSS is based on real-time sensor data and historical electronic health record (...
An adverse drug effect mentions extraction method based on weighted online recurrent extreme learning machine.
Computer methods and programs in biomedicine
Apr 30, 2019
BACKGROUND AND OBJECTIVE: Automatic extraction of adverse drug effect (ADE) mentions from biomedical texts is a challenging research problem that has attracted significant attention from the pharmacovigilance and biomedical text mining communities. I...
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