Text mining open datasets to support public health

Pita Costa, Joao; Stopar, luka; Fuart, Flavio; Grobelnik, Marko; Santanam, Raghu; Sun, Chenlu; Carlin, Paul; Black, Michaela and Wallace, Jonathan (2017). Text mining open datasets to support public health. In: Workshop on Information Technologies and Systems, 13-14 Dec 2017, Soeul.


Today’s society is data rich and information driven, with access to numerous data sources available that have the potential to provide new insights into areas such as disease prevention, personalised medicine and data driven policy decisions. This paper describes and demonstrates the use of text mining tools developed to support public health institutions to complement their data with other accessible open data sources, optimize
analysis and gain insight when examining policy. In particular we focus on the exploration of MEDLINE, the biggest structured open dataset of biomedical knowledge. In MEDLINE we utilize its terminology for indexing and cataloguing biomedical information – MeSH – to maximize the efficacy of the dataset.

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