Andreas Karwath

Klarigi identifies compositional and discriminatory ontology classes for groups of biomedical entities, providing semantic explanations that extend existing knowledge.

This paper develops a method to use uncurated clinical text phenotypes for differential diagnosis of common diseases using semantic similarity.

The paper develops a framework to extend ontologies using clinical text, improving their ability to characterize and classify medical data.

This paper introduces a method to predict cancer driver genes using ontology-based features and validates it in nasopharyngeal and colorectal cancers.

Vec2SPARQL integrates vector space representations with SPARQL queries to enable semantic similarity and classification within a single query for biomedical applications.