This paper is a natural prosecution of two previous works. We present a web geospatial framework for analyzing and monitoring the spatio-temporal evolution of disease hotspots. In order to detect the hotspots, we adopt Extended Fuzzy C-Means method which has been adapted for calculating spatial areas with high concentrations of events in a Geographic Information System and tested to study the spatial and temporal evolution of hotspot areas. Each event is given by the geo-positional coordinates of the place of residence of the patient. The analyst can insert event data directly on the map or digitizing the address of the residence of the patient and by using geo-coding services for locating the event. The events can be grouped for time intervals for studying the temporal evolution of the phenomenon. Other services allow the analyst to study the spatio-temporal evolution of the hotspot areas. In our experiments, the data consist of geo-referenced patterns corresponding to the residence of patients in the district of Naples (Italy) to whom a surgical intervention to the oto-laryngo-pharyngeal apparatus was carried out between the years 2008 -2012. The results show the presence of two major hotspots for every type of oto-laryngo-pharyngeal disease, the former covering a geographical area that affects the city of Naples, the latter covering various towns around Vesuvius. Both hotspots are significantly increased in recent years.

WebGIS platform for detecting spatio-temporal hotspots of oto-laryngo-pharyngeal diseases / Di Martino, Ferdinando; Mele, Roberta; Sessa, Salvatore; Barillari, Umberto E. S.; Barillari, Maria Rosaria. - (2014), pp. 112-118. (Intervento presentato al convegno 6th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014 tenutosi a University of Salerno, ita nel 2014) [10.1109/INCoS.2014.72].

WebGIS platform for detecting spatio-temporal hotspots of oto-laryngo-pharyngeal diseases

MELE, ROBERTA;
2014

Abstract

This paper is a natural prosecution of two previous works. We present a web geospatial framework for analyzing and monitoring the spatio-temporal evolution of disease hotspots. In order to detect the hotspots, we adopt Extended Fuzzy C-Means method which has been adapted for calculating spatial areas with high concentrations of events in a Geographic Information System and tested to study the spatial and temporal evolution of hotspot areas. Each event is given by the geo-positional coordinates of the place of residence of the patient. The analyst can insert event data directly on the map or digitizing the address of the residence of the patient and by using geo-coding services for locating the event. The events can be grouped for time intervals for studying the temporal evolution of the phenomenon. Other services allow the analyst to study the spatio-temporal evolution of the hotspot areas. In our experiments, the data consist of geo-referenced patterns corresponding to the residence of patients in the district of Naples (Italy) to whom a surgical intervention to the oto-laryngo-pharyngeal apparatus was carried out between the years 2008 -2012. The results show the presence of two major hotspots for every type of oto-laryngo-pharyngeal disease, the former covering a geographical area that affects the city of Naples, the latter covering various towns around Vesuvius. Both hotspots are significantly increased in recent years.
2014
6th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014
Carcinoma disease; Extended Fuzzy C-means; Fuzzy clustering; Hotspot; WEBGIS; Artificial Intelligence; Computer Networks and Communications
04 Pubblicazione in atti di convegno::04c Atto di convegno in rivista
WebGIS platform for detecting spatio-temporal hotspots of oto-laryngo-pharyngeal diseases / Di Martino, Ferdinando; Mele, Roberta; Sessa, Salvatore; Barillari, Umberto E. S.; Barillari, Maria Rosaria. - (2014), pp. 112-118. (Intervento presentato al convegno 6th International Conference on Intelligent Networking and Collaborative Systems, IEEE INCoS 2014 tenutosi a University of Salerno, ita nel 2014) [10.1109/INCoS.2014.72].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/856685
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