A novel shiny platform for the geo-spatial analysis of large amount of patient data.
- Published
- Accepted
- Subject Areas
- Data Science, Spatial and Geographic Information Systems
- Keywords
- Business Intelligence, GIS, RStudio, Healt data, Big Data, Geo-statistical analysis
- Copyright
- © 2017 Guarino et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2017. A novel shiny platform for the geo-spatial analysis of large amount of patient data. PeerJ Preprints 5:e3335v1 https://doi.org/10.7287/peerj.preprints.3335v1
Abstract
It has been estimated that up to 80% of all data stored in health care databases may have spatial components. To fully exploit such components, there is a need of improving existing tools or developing novel spatio-temporal functionalities. Geographic information systems (GIS) as QuantumGis, SOLAP2, etc. are potential candidates to support decisional needs, but despite their capabilities, they are still scarcely employed in association within BI applications. For these reasons, we are developing a GIS user-friendly interface in R environment in order to dynamically and interactively visualize and analyze (within BI platforms) diverse informative data layers (e.g., pathology incidence data, environmental pollution, etc.). Although preliminary, we believe that this kind of tools could be suitable used for epidemiologic, environmental and economical studies by providing geographical maps and statistical data analyses of interest for different stakeholders.
Author Comment
This is an abstract which has been accepted for the NETTAB 2017 Workshop