Cloud Computing in Healthcare and Biomedicine

Calabrese, Barbara; Cannataro, Mario

doi:10.12694/scpe.v16i1.1057

Cited by 50 publications

(23 citation statements)

References 67 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, wireless sensor networks or utilities for collect and process information from the "cloud" are used in health care institutions [15], [16]. Cloud Computing represents a simple but powerful distributed computing model that also supports communication protocols with devices, secure data access protocols and information privacy, important aspects in fields as medicine [13].…”

Section: Related Workmentioning

confidence: 99%

“…In this sense, Big Data analysis methods are providing effective solutions in the field of medicine [5]. For example in [16] it is presented a study focused on the new challenges in biomedicine for processing and storing large volumes of data from magnetic resonance imaging, etc. According to [16], US President Obama (2015) announced "the Precision Medicine Initiative", efforts to focus attention on what they called "the medicine of precision" which is based in doctor's experience and capabilities, and also in the infrastructure and information technology available in the modern world.…”

Section: Related Workmentioning

confidence: 99%

“…For example in [16] it is presented a study focused on the new challenges in biomedicine for processing and storing large volumes of data from magnetic resonance imaging, etc. According to [16], US President Obama (2015) announced "the Precision Medicine Initiative", efforts to focus attention on what they called "the medicine of precision" which is based in doctor's experience and capabilities, and also in the infrastructure and information technology available in the modern world. This initiative seeks to promote the development of infrastructures and innovative technologies to improve individual well-being health and treatment of diseases in society.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

An Intelligent System Prototype to support and sharing diagnoses of maligned tumours, based on personalized medicine philosophy

Fonseca¹,

Quelopana²

2016

View full text Add to dashboard Cite

Abstract. Circulatory systems diseases are one of the most important causes of death in Chilean population according to a report presented by the Chilean National Bureau of Statistics (INE). Undoubtedly, these sad numbers arise an opportunity to analyze ways to improve this situation. Personalized Medicine is a new approach used by health professionals to adapt standard medical treatments to patients' individual characteristics. Currently, several types of personalized-medicine software applications are built using Artificial Intelligent techniques and supported by techniques as Cloud Computing and Big Data. This architecture provides complex and varied information access such as clinical data, genome data, patients' treatment or drugs information, among others. This document describes a proposal to produce a method for generating and sharing medical information, particularly of maligned tumors in Chile. The prototype will be developed within the framework of the personalized medicine philosophy.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

An Intelligent System Prototype to support and sharing diagnoses of maligned tumours, based on personalized medicine philosophy

Fonseca¹,

Quelopana²

2016

View full text Add to dashboard Cite

show abstract

“…Due to the current Big data exponential data growth, solutions that store, process [10] and manage medical data are of a great interest. In this direction, cloud computing represents a cost-effective solution for such needs [1,2]. For instance, Marzini et al[23] make use of the cloud elasticity to manage basic activities in healthcare scenarios.…”

mentioning

confidence: 99%

“…Cloud computing offers a suitable platform for such collaborations [1]. For instance, the storage service offered by the Cloud can be considered as a shared pool where medical organisations can store and share their data.…”

mentioning

confidence: 99%

Analysis and Verification of XACML Policies in a Medical Cloud Environment

Ayache¹,

Erradi²,

Khoumsi³

et al. 2016

SCPE

View full text Add to dashboard Cite

The connectivity of devices, machines and people via Cloud infrastructure can support collaborations among doctors and specialists from different medical organisations. Such collaborations may lead to data sharing and joint tasks and activities. Hence, the collaborating organisations are responsible for managing and protecting data they share. Therefore, they should define a set of access control policies regulating the exchange of data they own. However, existing Cloud services do not offer tools to analyse these policies. In this paper, we propose a Cloud Policy Verification Service (CPVS ) for the analysis and the verification of access control policies specified using XACML. The analysis process detects anomalies at two policy levels: a) intra-policy: detects discrepancies between rules within a single security policy (conflicting rules and redundancies), and b) interpolicies: detects anomalies between several security policies such as inconsistency and similarity. The verification process consists in verifying the completeness property which guarantees that each access request is either accepted or denied by the access control policy. In order to demonstrate the efficiency of our method, we also provide the time and space complexities. Finally, we present the implementation of our method and demonstrate how efficiently our approach can detect policy anomalies. . Related Work. In a collaborative healthcare process, doctors and specialists from different medical organisations share patient's data in order to make a better diagnosis. Due to the current Big data exponential data growth, solutions that store, process [10] and manage medical data are of a great interest. In this direction, cloud computing represents a cost-effective solution for such needs [1,2]. For instance, Marzini et al.[23] make use of the cloud elasticity to manage basic activities in healthcare scenarios. On the other hand, the usage of cloud computing for medical environments raises several issues such as reliability and security.Regarding the reliability issue, Gawanmeh et al. [14] present a state of the art review on the verification of reliability in healthcare systems using either simulation-based verification, formal methods such as automata and prism [28,29], or semi-formal methods. In the work presented in this paper, we focus on the formal verification of the security aspect, especially access control.Access control protects the system's resources against unauthorized access via a set of policies. Jansen [18] proposed XACML as a policy specification language for cloud applications. Yet, XACML policies may contain conflicting and redundant rules, since XACML policies are sometimes managed by more than one administrator [16]. Moreover, in collaborative applications, the XACML policies are aggregated from collaborative parties which may raise conflicts between rules in different policies.Several works make use of verification techniques such as model checking in order to detect XACML policy anomalies. For instance, to detect conflicts...

show abstract

Bioinformatics and Microarray Data Analysis on the Cloud

Calabrese

Cannataro

2015

Methods in Molecular Biology

Self Cite

View full text Add to dashboard Cite

High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, 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 chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

show abstract

Cloud Computing in Healthcare and Biomedicine

Cited by 50 publications

References 67 publications

An Intelligent System Prototype to support and sharing diagnoses of maligned tumours, based on personalized medicine philosophy

An Intelligent System Prototype to support and sharing diagnoses of maligned tumours, based on personalized medicine philosophy

Analysis and Verification of XACML Policies in a Medical Cloud Environment

Bioinformatics and Microarray Data Analysis on the Cloud

Contact Info

Product

Resources

About