Extracting Disease-Phenotype Relations from Text with Disease-Phenotype Concept Recognisers and Association Rule Mining

Automatically extracting phenotypes (i.e., the composite of ones observable characteristics/traits) from free text such as scientific literature or clinical notes and associating phenotypes with diseases is an important task. Such associations can be used in, for example, recommending candidate genes for diseases, investigating drug targets, or performing differential diagnosis. In this paper, we focus on extracting disease-phenotype relations with association rule mining techniques and compare results with two other methods. We show that association rule mining offers promising alternative method for detecting disease-phenotype relations.