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.).

DOI: https://doi.org/10.1145/3219819

Abstract

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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