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What Do the Data Say in 10 Years of Pneumonia Victims? A Geo-Spatial Data Analytics Perspective

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Information Technology in Bio- and Medical Informatics (ITBAM 2016)

Abstract

The need to integrate, store, process and analyse data is continuously growing as information technologies facilitate the collection of vast amounts of data. These data can be in different repositories, have different data formats and present data quality issues, requiring the adoption of appropriate strategies for data cleaning, integration and storage. After that, suitable data analytics and visualization mechanisms can be used for the analysis of the available data and for the identification of relevant knowledge that support the decision-making process. This paper presents a data analytics perspective over 10 years of pneumonia incidence in Portugal, pointing the evolution and characterization of the mortal victims of this disease. The available data about the individuals was complemented with statistical data of the country, in order to characterize the overall incidence of this disease, following a spatial analysis and visualization perspective that is supported by several analytical dashboards.

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References

  1. Chen, H., Chiang, R.H., Storey, V.C.: Business intelligence and analytics: from big data to big impact. MIS Q. 36, 1165–1188 (2012)

    Google Scholar 

  2. Kimball, R., Ross, M.: The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. John Wiley & Sons Inc., Indianapolis (2013)

    Google Scholar 

  3. Abelló, A., Darmont, J., Etcheverry, L., Golfarelli, M., Mazón, J.-N., Naumann, F., Pedersen, T., Rizzi, S.B., Trujillo, J., Vassiliadis, P., Vossen, G.: Fusion cubes: towards self-service business intelligence. Int. J. Data Warehouse. Mining 9, 66–88 (2013)

    Article  Google Scholar 

  4. Han, J., Kamber, M., Pei, J.: Data Mining: Concept and Techniques. Morgan Kaufmann Publishers, San Francisco (2012)

    Book  MATH  Google Scholar 

  5. Viswanathan, G., Schneider, M.: On the requirements for user-centric spatial data warehousing and SOLAP. In: Xu, J., Yu, G., Zhou, S., Unland, R. (eds.) DASFAA Workshops 2011. LNCS, vol. 6637, pp. 144–155. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  6. Rivest, S., Bédard, Y., Proulx, M.-J., Nadeau, M., Hubert, F., Pastor, J.: SOLAP technology: merging business intelligence with geospatial technology for interactive spatio-temporal exploration and analysis of data. ISPRS J. Photogrammetry Remote Sensing 60, 17–33 (2005)

    Article  Google Scholar 

  7. Santos, M.Y., Leite, V., Carvalheira, A., de Araújo, A.T., Cruz, J.: Characterization of pneumonia incidence supported by a business intelligence system. In: Ortuño, F., Rojas, I. (eds.) IWBBIO 2015, Part I. LNCS, vol. 9043, pp. 30–41. Springer, Heidelberg (2015)

    Google Scholar 

  8. Eurostat: Respiratory diseases statistics, June 2016. http://ec.europa.eu/eurostat/statistics-explained/index.php/Respiratory_diseases_statistics

  9. WHO: World Health Organization. “The top 10 causes of death.” 27 May 2015 (2015). http://who.int/mediacentre/factsheets/fs310/en/

  10. Sufahani, S.F., Razali, S.N.A.M., Mormin, M.F., Khamis, A.: An analysis of the prevalence of pneumonia for children under 12 year old in Tawau general hospital, Malaysia. In: Proceedings of the International Seminar on the Application of Science & Mathematics, Kuala Lumpur (2011)

    Google Scholar 

  11. Oroszi, F., Ruhland, J.: An early warning system for hospital acquired pneumonia. In: Proceedings of the 18th European Conference on Information Systems (2010)

    Google Scholar 

  12. Trillo-Alvarez, C., Cartin-Ceba, R., Kor, D.J., Kojicic, M., Kashyap, R., Thakur, S., Thakur, L., Herasevich, V., Malinchoc, M., Gajic, O.: Acute lung injury prediction score: derivation and validation in a population-based sample. Eur. Respir. J. 37, 604–609 (2011)

    Article  Google Scholar 

  13. Wu, C., Rosenfeld, R., Clermont, G.: Using data-driven rules to predict mortality in severe community acquired pneumonia. PLoS ONE 9, e89053 (2014)

    Article  Google Scholar 

  14. Peng, R.: Exploratory data analysis with R (2015). http://Lulu.com

  15. Tufte, E.R.: Beautiful Evidence, 1st edn. Graphics Press, Cheshire (2006)

    Google Scholar 

  16. Tufte, E.R., Graves-Morris, P.R.: The Visual Display of Quantitative Information. Graphics press, Cheshire (1983)

    Google Scholar 

  17. INE: Portugal census (2011). http://censos.ine.pt

  18. Santos, M.Y., Carvalheira, A., de Araujo, A.T.: A data-driven analytics approach in the study of pneumonia’s fatalities. In: IEEE International Conference on Data Science and Advanced Analytics (DSAA), 36678 2015, pp. 1–10. IEEE (2015)

    Google Scholar 

  19. R-project: the R project for statistical computing (2016). https://www.r-project.org

  20. Tableau (2016). http://www.tableau.com

Download references

Acknowledgement

This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.

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Correspondence to Maribel Yasmina Santos .

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Santos, M.Y., Santos, A.C., de Araújo, A.T. (2016). What Do the Data Say in 10 Years of Pneumonia Victims? A Geo-Spatial Data Analytics Perspective. In: Renda, M., Bursa, M., Holzinger, A., Khuri, S. (eds) Information Technology in Bio- and Medical Informatics. ITBAM 2016. Lecture Notes in Computer Science(), vol 9832. Springer, Cham. https://doi.org/10.1007/978-3-319-43949-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-43949-5_1

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