Mining MEDLINE for the visualisation of a global perspective on biomedical knowledge

Costa, Joao Pita; Stopar, Luka; Fuart, Flavio; Grobelnik, Marko; Santanam, Raghu; Chenlu, Sun; Carlin, Paul; Black, Michaela and Wallace, Jonathan (2018). Mining MEDLINE for the visualisation of a global perspective on biomedical knowledge. In: KDD '18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Yike, Yike and Farooq, Faisal eds.).



There is an ever increasing number of data sources that potentially could be used to gain new insights into areas such as disease prevention, policy formulation/evaluation and personalised medicine, but these are not optimised for use within an analytics type user interface. The MIDAS project was funded under a call for ‘Big Data supporting Public Health policies’ to develop a big data platform that facilitates the utilisation of healthcare data beyond existing isolated systems, making that data amenable to enrichment with open and social data. This aligns closely with a number of themes in Knowledge Discovery in Databases (KDD) in that the platform enables the integration of heterogeneous data sources, providing privacy-preserving analytics, forecasting tools and visualisation modules to deliver actionable information. Policy makers as a result will have the capability to perform data-driven evaluations of the efficiency and effectiveness of proposed policies in terms of expenditure, delivery, wellbeing, and health and socio-economic inequalities, thus improving current policy formulation, delivery risk stratification and evaluation. This H2020 project has a total of 15 partners from 5 EU countries as well as Arizona State University (ASU). The partners are Universities, SMEs and health departments in governmental institutions.

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