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.
|Title of host publication||Proceedings of CIBB 2014|
|Publication status||Published - 2014|
|Event||11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB) - Computer Laboratory, University Of Cambridge, Cambridge, United Kingdom|
Duration: 26 Jun 2014 → 28 Jun 2014
|Conference||11th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics (CIBB)|
|Abbreviated title||CIBB 2014|
|Period||26/06/14 → 28/06/14|