On The Correlation Between Geo-Referenced Clinical Data And Remotely Sensed Air Pollution Maps.
Stud Health Technol Inform
; 216: 1048, 2015.
Article
em En
| MEDLINE
| ID: mdl-26262347
ABSTRACT
This work presents an analysis framework enabling the integration of a clinical-administrative dataset of Type 2 Diabetes (T2D) patients with environmental information derived from air quality maps acquired from remote sensing data. The research has been performed within the EU project MOSAIC, which gathers T2D patients' data coming from Fondazione S. Maugeri (FSM) hospital and the Pavia local health care agency (ASL). The proposed analysis is aimed to highlight the complexity of the domain, showing the different perspectives that can be adopted when applying a data-driven approach to large variety of temporal, geo-localized data. We investigated a set of 899 patients, located in the Pavia area, and detected several patterns depicting how clinical facts and air pollution variations may be related.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Vigilância da População
/
Sistemas de Informação Geográfica
/
Diabetes Mellitus Tipo 2
/
Poluição do Ar
/
Tecnologia de Sensoriamento Remoto
/
Hospitalização
Tipo de estudo:
Etiology_studies
/
Prevalence_studies
/
Risk_factors_studies
/
Screening_studies
Limite:
Humans
País/Região como assunto:
Europa
Idioma:
En
Revista:
Stud Health Technol Inform
Assunto da revista:
INFORMATICA MEDICA
/
PESQUISA EM SERVICOS DE SAUDE
Ano de publicação:
2015
Tipo de documento:
Article
País de afiliação:
Itália