On the Correlation between Geo-Referenced Clinical Data and Remotely Sensed Air Pollution Maps

Arianna Dagliati; Andrea Marinoni; Carlo Cerra; Paolo Gamba; Riccardo Bellazzi

doi:10.3233/978-1-61499-564-7-1048

On the Correlation between Geo-Referenced Clinical Data and Remotely Sensed Air Pollution Maps

Arianna Dagliati, Andrea Marinoni, Carlo Cerra, Paolo Gamba, Riccardo Bellazzi

Istituti Clinici Scientifici Maugeri Spa – Società Benefit

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Studies in Health Technology and Informatics
Publisher	IOS Press
Pages	1048
Number of pages	1
Volume	216
ISBN (Print)	9781614995630
DOIs	https://doi.org/10.3233/978-1-61499-564-7-1048
Publication status	Published - 2015
Event	15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 - Sao Paulo, Brazil Duration: Aug 19 2015 → Aug 23 2015

Publication series

Name	Studies in Health Technology and Informatics
Volume	216
ISSN (Print)	09269630
ISSN (Electronic)	18798365

Other

Other	15th World Congress on Health and Biomedical Informatics, MEDINFO 2015
Country/Territory	Brazil
City	Sao Paulo
Period	8/19/15 → 8/23/15

Keywords

Air pollution maps
Environmental factors
Geo-referenced data
Type 2 Diabetes

ASJC Scopus subject areas

Biomedical Engineering
Health Informatics
Health Information Management

Access to Document

10.3233/978-1-61499-564-7-1048

Cite this

On the Correlation between Geo-Referenced Clinical Data and Remotely Sensed Air Pollution Maps. / Dagliati, Arianna; Marinoni, Andrea; Cerra, Carlo; Gamba, Paolo; Bellazzi, Riccardo.

Studies in Health Technology and Informatics. Vol. 216 IOS Press, 2015. p. 1048 (Studies in Health Technology and Informatics; Vol. 216).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Dagliati, A, Marinoni, A, Cerra, C, Gamba, P & Bellazzi, R 2015, On the Correlation between Geo-Referenced Clinical Data and Remotely Sensed Air Pollution Maps. in Studies in Health Technology and Informatics. vol. 216, Studies in Health Technology and Informatics, vol. 216, IOS Press, pp. 1048, 15th World Congress on Health and Biomedical Informatics, MEDINFO 2015, Sao Paulo, Brazil, 8/19/15. https://doi.org/10.3233/978-1-61499-564-7-1048

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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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AB - 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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On the Correlation between Geo-Referenced Clinical Data and Remotely Sensed Air Pollution Maps

Abstract

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Keywords

ASJC Scopus subject areas

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