AIMC Topic: Semantics

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Evaluating semantic relations in neural word embeddings with biomedical and general domain knowledge bases.

BMC medical informatics and decision making
BACKGROUND: In the past few years, neural word embeddings have been widely used in text mining. However, the vector representations of word embeddings mostly act as a black box in downstream applications using them, thereby limiting their interpretab...

Deep neural models for extracting entities and relationships in the new RDD corpus relating disabilities and rare diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: There is a huge amount of rare diseases, many of which have associated important disabilities. It is paramount to know in advance the evolution of the disease in order to limit and prevent the appearance of disabilities and ...

Consistent Semantic Annotation of Outdoor Datasets via 2D/3D Label Transfer.

Sensors (Basel, Switzerland)
The advance of scene understanding methods based on machine learning relies on the availability of large ground truth datasets, which are essential for their training and evaluation. Construction of such datasets with imagery from real sensor data ho...

Chemical-induced disease relation extraction with dependency information and prior knowledge.

Journal of biomedical informatics
Chemical-disease relation (CDR) extraction is significantly important to various areas of biomedical research and health care. Nowadays, many large-scale biomedical knowledge bases (KBs) containing triples about entity pairs and their relations have ...

A deep learning approach to bilingual lexicon induction in the biomedical domain.

BMC bioinformatics
BACKGROUND: Bilingual lexicon induction (BLI) is an important task in the biomedical domain as translation resources are usually available for general language usage, but are often lacking in domain-specific settings. In this article we consider BLI ...

Using data-driven sublanguage pattern mining to induce knowledge models: application in medical image reports knowledge representation.

BMC medical informatics and decision making
BACKGROUND: The use of knowledge models facilitates information retrieval, knowledge base development, and therefore supports new knowledge discovery that ultimately enables decision support applications. Most existing works have employed machine lea...

Semantic measures: Using natural language processing to measure, differentiate, and describe psychological constructs.

Psychological methods
Psychological constructs, such as emotions, thoughts, and attitudes are often measured by asking individuals to reply to questions using closed-ended numerical rating scales. However, when asking people about their state of mind in a natural context ...

Multi-Factored Gene-Gene Proximity Measures Exploiting Biological Knowledge Extracted from Gene Ontology: Application in Gene Clustering.

IEEE/ACM transactions on computational biology and bioinformatics
To describe the cellular functions of proteins and genes, a potential dynamic vocabulary is Gene Ontology (GO), which comprises of three sub-ontologies namely, Biological-process, Cellular-component, and Molecular-function. It has several application...

Medical concept normalization in social media posts with recurrent neural networks.

Journal of biomedical informatics
Text mining of scientific libraries and social media has already proven itself as a reliable tool for drug repurposing and hypothesis generation. The task of mapping a disease mention to a concept in a controlled vocabulary, typically to the standard...

DeepText2GO: Improving large-scale protein function prediction with deep semantic text representation.

Methods (San Diego, Calif.)
As of April 2018, UniProtKB has collected more than 115 million protein sequences. Less than 0.15% of these proteins, however, have been associated with experimental GO annotations. As such, the use of automatic protein function prediction (AFP) to r...