BERT based clinical knowledge extraction for biomedical knowledge graph construction and analysis

A Knowledge Extraction Framework for Biomedical Pathways

In this paper we present a novel knowledge extraction framework that is based on semantic parsing. The semantic information originates in a variety of resources, but one in particular, namely BioFrameNet, is central to the characterization of complex events and processes that form biomedical pathways. The paper discusses the promising results of semantic parsing and explains how these results c...

Knowledge-Based Graph Exploration Analysis

In a context where graph transformation is used to explore a space of possible solutions to a given problem, it is almost always necessary to inspect candidate solutions for relevant properties. This means that there is a need for a flexible mechanism to query not only graphs but also their evolution. In this paper we show how to use Prolog queries to analyse graph exploration. Queries can oper...

Online Inference for Knowledge Graph Construction

The task of knowledge graph construction presents a confounding challenge for statistical relational models. While the uncertainty of extractions from NLP tools and the ontological structure of knowledge are a perfect match for the strengths of statistical relational techniques, the vast and continually growing evidence from which knowledge graphs are constructed can make such models prohibitiv...

Toward Ontology-Based Knowledge Extraction from Biomedical Literature

Knowledge extraction and data mining algorithms for complex biomedical data

Due to the advances of high throughput technologies for data acquisition in biomedicine an increasing amount of data is produced. This thesis proposes innovative algorithms for data mining on biomedical data ranging from clustering via semi-supervised clustering to classification. Clustering aims at deriving a previously unknown grouping of a data set and can be applied e.g. to investigate diff...