The efficient management and analysis of patient data enrolled in clinical studies is a critical factor for both supporting data management and knowledge discovery from data. Recent trends in literature present many approaches that demonstrate that the integration of multiple data sources (e.g. biochemical parameters, geographical data as well as the behaviour of patients into social networks) may improve the quality of findings. Moreover, the collection of such data may enable the development of a tailored intervention for precision medicine. All these aspects rely on the design and development of novel solutions for data management, storing and consequently, analysis. We here report the design and development of a prototype for data management and sharing introduced during a collaboration of Bioinformatics Laboratory, the Fisiopatology Unit and the University Hospital of Catanzaro. Our findings are currently under the validation of the clinicians.

A Framework for Patient Data Management and Analysis in Randomised Clinical Trials

Guzzi P. H.;Veltri P.
2020-01-01

Abstract

The efficient management and analysis of patient data enrolled in clinical studies is a critical factor for both supporting data management and knowledge discovery from data. Recent trends in literature present many approaches that demonstrate that the integration of multiple data sources (e.g. biochemical parameters, geographical data as well as the behaviour of patients into social networks) may improve the quality of findings. Moreover, the collection of such data may enable the development of a tailored intervention for precision medicine. All these aspects rely on the design and development of novel solutions for data management, storing and consequently, analysis. We here report the design and development of a prototype for data management and sharing introduced during a collaboration of Bioinformatics Laboratory, the Fisiopatology Unit and the University Hospital of Catanzaro. Our findings are currently under the validation of the clinicians.
2020
978-1-7281-6215-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/362462
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