Title
A Novel Approach for Clinical Data Harmonization.
Abstract
A city transforms into a “smart” one when it utilizes the data from smart devices, cloud infrastructures, applications and repositories in order to develop and provide new services, products and insights with the goal being to offer a safer, more efficient and robust environment for government, citizens and businesses, and accelerate sustainable economic growth. Although the variability across cities in terms of cultural background, demographics, current infrastructures, topology, among others, might drive significant variations in the individual goals of a smart city, the role of health in achieving the aforementioned goals is of paramount importance in any city. One of the starting points of introducing a health-related orientation into a smart city developments and operations is the intelligent processing of the overwhelming amount of clinical data being continuously generated during healthcare provision, daily activities and clinical research. Great challenges that need to be met in order to offer big data analytics over clinical data for the purposes of a smart city lie in their high heterogeneity at system, syntactic, structural and semantic level as well as their sensitive nature from the legal and ethical perspective, which may prevent and/or limit access to and analysis of the data. In this work we will present a novel approach for expressing clinical data using a common formalism with explicit semantics of the terms being used. Based on this established semantic ground, questions on health-related data can be placed for disease prevention, treatment monitoring, post-marketing surveillance, policy making, among others.
Year
DOI
Venue
2019
10.1109/BIGCOMP.2019.8679239
BigComp
Keywords
Field
DocType
Ontologies,Tools,Smart cities,Diseases,Government,Metadata
Data science,Ontology (information science),Metadata,Computer science,SAFER,Smart city,Big data,Semantics,Government,Cloud computing
Conference
ISSN
ISBN
Citations 
2375-933X
978-1-5386-7789-6
0
PageRank 
References 
Authors
0.34
0
4