Health Mining: a new data fusion and integration paradigm

Alessandro Di Stefano, Aurelio La Corte, Marialisa Scatá

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Abstract

One of the future challenges of information and communication technology (ICT) is particularly targeted at public health and clinical interventions management. The aim is to make smart the management and the processes that characterize this context to optimize the procedures and provide technological support. In this paper we propose the starting point of a new approach through architecture to introduce methodologies for fusing, integrating and drawing inference from a plurality of clinical, social and Internet of Things data, extracted from different sources. Health Mining is the central node of the proposed architecture and serves as a knowledge base for bio-inspired systems to support and perform the diagnostic process; this approach is better than the one applied with a plurality of disgregated data.
Original languageEnglish
Title of host publicationProceedings of CIBB 2014
EditorsRoberto Tagliaferri
Publication statusPublished - 2014
Event11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB) - Computer Laboratory, University Of Cambridge, Cambridge, United Kingdom
Duration: 26 Jun 201428 Jun 2014

Conference

Conference11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB)
Abbreviated titleCIBB 2014
Country/TerritoryUnited Kingdom
CityCambridge
Period26/06/1428/06/14

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