AI Medical Compendium Topic:
Semantics

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Knowledge Discovery from Biomedical Ontologies in Cross Domains.

PloS one
In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability s...

Medical Image Analysis by Cognitive Information Systems - a Review.

Journal of medical systems
This publication presents a review of medical image analysis systems. The paradigms of cognitive information systems will be presented by examples of medical image analysis systems. The semantic processes present as it is applied to different types o...

Biomedical event trigger detection by dependency-based word embedding.

BMC medical genomics
BACKGROUND: In biomedical research, events revealing complex relations between entities play an important role. Biomedical event trigger identification has become a research hotspot since its important role in biomedical event extraction. Traditional...

MeSH-Informed Enrichment Analysis and MeSH-Guided Semantic Similarity Among Functional Terms and Gene Products in Chicken.

G3 (Bethesda, Md.)
Biomedical vocabularies and ontologies aid in recapitulating biological knowledge. The annotation of gene products is mainly accelerated by Gene Ontology (GO), and more recently by Medical Subject Headings (MeSH). Here, we report a suite of MeSH pack...

Using AberOWL for fast and scalable reasoning over BioPortal ontologies.

Journal of biomedical semantics
BACKGROUND: Reasoning over biomedical ontologies using their OWL semantics has traditionally been a challenging task due to the high theoretical complexity of OWL-based automated reasoning. As a consequence, ontology repositories, as well as most oth...

Event Recognition Based on Deep Learning in Chinese Texts.

PloS one
Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features u...

TopoICSim: a new semantic similarity measure based on gene ontology.

BMC bioinformatics
BACKGROUND: The Gene Ontology (GO) is a dynamic, controlled vocabulary that describes the cellular function of genes and proteins according to tree major categories: biological process, molecular function and cellular component. It has become widely ...

Ensembles of randomized trees using diverse distributed representations of clinical events.

BMC medical informatics and decision making
BACKGROUND: Learning deep representations of clinical events based on their distributions in electronic health records has been shown to allow for subsequent training of higher-performing predictive models compared to the use of shallow, count-based ...

A method for exploring implicit concept relatedness in biomedical knowledge network.

BMC bioinformatics
BACKGROUND: Biomedical information and knowledge, structural and non-structural, stored in different repositories can be semantically connected to form a hybrid knowledge network. How to compute relatedness between concepts and discover valuable but ...

NeuroRDF: semantic integration of highly curated data to prioritize biomarker candidates in Alzheimer's disease.

Journal of biomedical semantics
BACKGROUND: Neurodegenerative diseases are incurable and debilitating indications with huge social and economic impact, where much is still to be learnt about the underlying molecular events. Mechanistic disease models could offer a knowledge framewo...