AI Medical Compendium Journal:
Journal of biomedical semantics

Showing 51 to 60 of 193 articles

An integrative knowledge graph for rare diseases, derived from the Genetic and Rare Diseases Information Center (GARD).

Journal of biomedical semantics
BACKGROUND: The Genetic and Rare Diseases (GARD) Information Center was established by the National Institutes of Health (NIH) to provide freely accessible consumer health information on over 6500 genetic and rare diseases. As the cumulative scientif...

De-identifying free text of Japanese electronic health records.

Journal of biomedical semantics
BACKGROUND: Recently, more electronic data sources are becoming available in the healthcare domain. Electronic health records (EHRs), with their vast amounts of potentially available data, can greatly improve healthcare. Although EHR de-identificatio...

Structuring, reuse and analysis of electronic dental data using the Oral Health and Disease Ontology.

Journal of biomedical semantics
BACKGROUND: A key challenge for improving the quality of health care is to be able to use a common framework to work with patient information acquired in any of the health and life science disciplines. Patient information collected during dental care...

Identifying disease trajectories with predicate information from a knowledge graph.

Journal of biomedical semantics
BACKGROUND: Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses that identify e.g. relationships between diseases. Some diseases are often dia...

CAS: corpus of clinical cases in French.

Journal of biomedical semantics
BACKGROUND: Textual corpora are extremely important for various NLP applications as they provide information necessary for creating, setting and testing those applications and the corresponding tools. They are also crucial for designing reliable meth...

The African wildlife ontology tutorial ontologies.

Journal of biomedical semantics
BACKGROUND: Most tutorial ontologies focus on illustrating one aspect of ontology development, notably language features and automated reasoners, but ignore ontology development factors, such as emergent modelling guidelines and ontological principle...

Combining lexical and context features for automatic ontology extension.

Journal of biomedical semantics
BACKGROUND: Ontologies are widely used across biology and biomedicine for the annotation of databases. Ontology development is often a manual, time-consuming, and expensive process. Automatic or semi-automatic identification of classes that can be ad...

OHMI: the ontology of host-microbiome interactions.

Journal of biomedical semantics
BACKGROUND: Host-microbiome interactions (HMIs) are critical for the modulation of biological processes and are associated with several diseases. Extensive HMI studies have generated large amounts of data. We propose that the logical representation o...

Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death.

Journal of biomedical semantics
BACKGROUND: Free text in electronic health records (EHR) may contain additional phenotypic information beyond structured (coded) information. For major health events - heart attack and death - there is a lack of studies evaluating the extent to which...

Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.

Journal of biomedical semantics
BACKGROUND: Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and integration of this knowledge...