CrowdHEALTH: Big Data Analytics and Holistic Health Records
| Autor: | Parisis, Gallos, Santiago, Aso, Serge, Autexier, Arturo, Brotons, Antonio, De Nigro, Gregor, Jurak, Athanasios, Kiourtis, Pavlos, Kranas, Dimosthenis, Kyriazis, Mitja, Lustrek, Andrianna, Magdalinou, Ilias, Maglogiannis, John, Mantas, Antonio, Martinez, Andreas, Menychtas, Lydia, Montandon, Florin, Picioroaga, Manuel, Perez, Dalibor, Stanimirovic, Gregor, Starc, Tanja, Tomson, Ruth, Vilar-Mateo, Ana-Maria, Vizitiu |
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| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Studies in health technology and informatics r-IIS La Fe. Repositorio Institucional de Producción Científica del Instituto de Investigación Sanitaria La Fe instname |
| ISSN: | 0926-9630 |
| Popis: | The aim of this paper is to present examples of big data techniques that can be applied on Holistic Health Records (HHR) in the context of the CrowdHEALTH project. Real-time big data analytics can be performed on the stored data (i.e. HHRs) enabling correlations and extraction of situational factors between laboratory exams, physical activities, biosignals, medical data patterns, and clinical assessment. Based on the outcomes of different analytics (e.g. risk analysis, pathways mining, forecasting and causal analysis) on the aforementioned HHRs datasets, actionable information can be obtained for the development of efficient health plans and public health policies. |
| Databáze: | OpenAIRE |
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