A Unified Medical Language System (UMLS) based system for Literature-Based Discovery in medicine.
Literature-Based Discovery (LBD) is a technique that can be used in translational research to connect the very sparse and huge information available in scientific publications in order to extract new knowledge. This paper presents an LBD system based on the open discovery paradigm exploiting NLP techniques and UMLS medical concepts mapping, to provide a set of tools useful to discover unknown relationships. The system has been evaluated on the problem of discovering new candidate genes potentially related to dilated cardiomyopathies (DCM), and can be used in any medical context to connect different type of concepts. The validation of the system involves reproducing the discovery of genes currently associated to DCM. Validation showed that the system is able to discover many gene-disease associations by using the literature available before their first publication in a scientific article.
Department of Industrial and Information Engineering, University of Pavia, Italy.
Matteo
M
Gabetta
Cristiana
C
Larizza
Riccardo
R
Bellazzi
D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D010506:Periodicals as Topic; D012660:Semantics; D009626:Terminology as Topic; D017432:Unified Medical Language System