AI Medical Compendium Topic:
Semantics

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Knowledge Author: facilitating user-driven, domain content development to support clinical information extraction.

Journal of biomedical semantics
BACKGROUND: Clinical Natural Language Processing (NLP) systems require a semantic schema comprised of domain-specific concepts, their lexical variants, and associated modifiers to accurately extract information from clinical texts. An NLP system leve...

Using the Semantic Web for Rapid Integration of WikiPathways with Other Biological Online Data Resources.

PLoS computational biology
The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using s...

Large scale biomedical texts classification: a kNN and an ESA-based approaches.

Journal of biomedical semantics
BACKGROUND: With the large and increasing volume of textual data, automated methods for identifying significant topics to classify textual documents have received a growing interest. While many efforts have been made in this direction, it still remai...

FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation.

Journal of biomedical semantics
BACKGROUND: Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that descr...

Topic detection using paragraph vectors to support active learning in systematic reviews.

Journal of biomedical informatics
Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to signi...

TaggerOne: joint named entity recognition and normalization with semi-Markov Models.

Bioinformatics (Oxford, England)
MOTIVATION: Text mining is increasingly used to manage the accelerating pace of the biomedical literature. Many text mining applications depend on accurate named entity recognition (NER) and normalization (grounding). While high performing machine le...

An ensemble method for extracting adverse drug events from social media.

Artificial intelligence in medicine
OBJECTIVE: Because adverse drug events (ADEs) are a serious health problem and a leading cause of death, it is of vital importance to identify them correctly and in a timely manner. With the development of Web 2.0, social media has become a large dat...

Generation of open biomedical datasets through ontology-driven transformation and integration processes.

Journal of biomedical semantics
BACKGROUND: Biomedical research usually requires combining large volumes of data from multiple heterogeneous sources, which makes difficult the integrated exploitation of such data. The Semantic Web paradigm offers a natural technological space for d...

The BioHub Knowledge Base: Ontology and Repository for Sustainable Biosourcing.

Journal of biomedical semantics
BACKGROUND: The motivation for the BioHub project is to create an Integrated Knowledge Management System (IKMS) that will enable chemists to source ingredients from bio-renewables, rather than from non-sustainable sources such as fossil oil and its d...

An Artificial Intelligence System to Predict Quality of Service in Banking Organizations.

Computational intelligence and neuroscience
Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly c...