Extraction of drug-disease relations from MEDLINE abstracts

Biological research literature, as in many other domains of human activity, is a rich source of knowledge. MEDLINE is a huge database of biomedical information and life sciences; it provides information in the form of abstracts and documents. However, extracting this information leads to various problems, related to the types of information such as recognition of all terms related to the domain of texts, concepts associated with them, as well as identifying the types of relationships. In this context, we suggest in this paper an approach to extract disease-drug relations: in a first step, we employ Natural Language Processing techniques for the abstracts' preprocessing. In a second step we extract a set of features from the preprocessed abstracts. Finally we extract a disease-drug relation using machine learning classifier.