Event-based Information Extraction for the biomedical domain: the Caderige project
Erick Alphonse (MIG), Sophie Aubin (LIPN), Philippe Bessi\`eres (MIG),, Gilles Bisson (Leibniz - IMAG), Thierry Hamon (LIPN), Sandrine Lagarrigue, (INRA-ENSAR), Adeline Nazarenko (LIPN), Alain-Pierre Manine (MIG), Claire, N\'edellec (MIG), Mohamed Ould Abdel Vetah (MIG)
TL;DR
The paper presents the Caderige project, which integrates biology, machine learning, and NLP to develop tools for extracting structured information from biomedical literature, especially Medline.
Contribution
It introduces a multidisciplinary approach for high-level information extraction in biomedicine, comparing it to existing methods.
Findings
Development of high-level analysis tools for Medline
Comparison with state-of-the-art methods
Interdisciplinary collaboration in biomedical information extraction
Abstract
This paper gives an overview of the Caderige project. This project involves teams from different areas (biology, machine learning, natural language processing) in order to develop high-level analysis tools for extracting structured information from biological bibliographical databases, especially Medline. The paper gives an overview of the approach and compares it to the state of the art.
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Taxonomy
TopicsBiomedical Text Mining and Ontologies · Semantic Web and Ontologies · Topic Modeling