sensitive data

healthcare systems

data healthcare

Scalable Computing. Practice and Experience

. High throughput platforms available in clinical settings or in research laboratories, such as magnetic resonance imaging, microarray, mass spectrometry and next-generation sequencing, are producing an increasing volume of clinical and omics data that poses new issues in terms of secure data storage, models for data integration and analysis, and high performance computing. Cloud Computing offers large scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and it supports easy but powerful distributed computing models, for facing those issues. In fact, in the recent years it has been adopted for the deployment of several applications in healthcare and bioinformatics both in academia and in the industry. However, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This paper reviews main cloud-based healthcare and biomedicine applications; with a special focus on healthcare, biomedicine and bioinformatics solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

Cloud Computing in Healthcare and Biomedicine