Clinical records (also known as Electronic Medical Records or EMRs) have been considered as a collection of patients health information. Elettronic Citizen Helth Records store information regarding life style, activities, habits, environment (i.e. water sources or air quality), routine health screening like blood biological analysis. Patients and providers stand to benefit from Internet of Things (IoT) in healthcare. Some uses of healthcare IoT are mobile medical applications or wearable devices that allow patients to capture their health data. Smart personal devices as well as data generator devices (i.e., internet of things) allow to provide such kind of data which may be collected in unique (cloud) database. Such information can then be related to location data within a geograPic context. We use clinical anonymized data extracted from a Biological Department of University Magna Graecia Hospital. We show how to include geograPic operators to statistical methods and how to analyze environmental data and citizen habits to improve wellness. We report on developing and testing a geo-based system to analyze biological data. (C) 2016 Published by Elsevier B.V.
Geoblood: a web based tool for geo-analysis of biological data
Guzzi P;Cuda G;Veltri Pierangelo
2016-01-01
Abstract
Clinical records (also known as Electronic Medical Records or EMRs) have been considered as a collection of patients health information. Elettronic Citizen Helth Records store information regarding life style, activities, habits, environment (i.e. water sources or air quality), routine health screening like blood biological analysis. Patients and providers stand to benefit from Internet of Things (IoT) in healthcare. Some uses of healthcare IoT are mobile medical applications or wearable devices that allow patients to capture their health data. Smart personal devices as well as data generator devices (i.e., internet of things) allow to provide such kind of data which may be collected in unique (cloud) database. Such information can then be related to location data within a geograPic context. We use clinical anonymized data extracted from a Biological Department of University Magna Graecia Hospital. We show how to include geograPic operators to statistical methods and how to analyze environmental data and citizen habits to improve wellness. We report on developing and testing a geo-based system to analyze biological data. (C) 2016 Published by Elsevier B.V.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.