Mobile healthcare information management utilizing Cloud Computing and Android OS

Doukas, Charalampos; Pliakas, Thomas; Maglogiannis, Ilias

doi:10.1109/iembs.2010.5628061

Cited by 233 publications

(107 citation statements)

References 8 publications

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“…Electronic Health records (EHR) paired with cloud computing systems brings a solution for the "big data" challenge where it accommodates storage resources and facilitates the process of sharing patients' data between healthcare providers. [17].…”

Section: Resultsmentioning

confidence: 99%

“…As it is illustrated in Figure 2, when patients want to access their own health records that are stored in cloud they connect to it through their mobile phones. There are imaging module that can be installed in mobile phones that can help display medical images by decoding them in DICOM format [15][16][17] (Figure 2). …”

Section: Digital Imaging Communication In Medicine and Cloud Computingmentioning

confidence: 99%

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Cloud Computing and Healthcare Services

Aziz¹,

Guled²

2016

J Biosens Bioelectron

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There is a significant volume of healthcare data generated daily. The data are important and vital for decision making and delivering the best care for patients. Cloud computing is a cost effective method that facilitates real-time data collection, data storage and exchange between healthcare organizations. Cloud infrastructure is characterized with a high throughput and a high volume storage; two important factors for efficient data analysis of large patients' population. Security and privacy are of the major concerns for using cloud-based healthcare services. Healthcare organization should have electronic medical records in order to use the cloud infrastructure. In order to cope with the rapid advancements in information technology and the utilization of cloud based services, efforts should be dedicated to move healthcare data form the traditional paper based to the electronic format. Then, regional legislation and policies should be enacted to regulate and control the usage of healthcare data.

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Section: Resultsmentioning

confidence: 99%

Section: Digital Imaging Communication In Medicine and Cloud Computingmentioning

confidence: 99%

Cloud Computing and Healthcare Services

Aziz¹,

Guled²

2016

J Biosens Bioelectron

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show abstract

“…These resources can be rapidly allocated or released depending on the current server demand either automatically (e.g., Amazon EC2) or manually. Cloud computing has been used in mobile healthcare services for several years now and it has been effectively demonstrated to ease development of health-related architectures [16]. Nevertheless, integrating these services with mobile platforms is far from trivial and that constitutes a different challenge altogether.…”

Section: Mobile Cloud Computing and Healthcare Servicesmentioning

confidence: 99%

Improving Healthcare Team Collaboration in Hospital Transfers through Cloud-Based Mobile Systems

Neyem

Carrillo

Jerez

et al. 2016

Mobile Information Systems

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It is a clinical fact that better patient flow management in and between hospitals improves quality of care, resource utilization, and cost efficiency. As the number of patients in hospitals constantly grows, the need for hospital transfers is directly affected. Interhospital transfers can be required for several reasons but they are most commonly made when the diagnostic and therapeutic facilities required for a patient are not available locally. Transferring a critical patient between hospitals is commonly associated with risk of death and complications. This raises the question: How can we improve healthcare team collaboration in hospital transfers through the use of emerging information technology and communication services? This paper presents a cloud-based mobile system for supporting team collaboration and decision-making in the transportation of patients in critical condition. The Rapid Emergency Medicine Score (REMS) scale was used as an outcome variable, being a useful scale to assess the risk profile of critical patients requiring transfers between hospitals. This helps medical staff to adopt proper risk-prevention measures when handling a transfer and to react on time if any complications arise in transit.

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“…Medical information management is a wide concept which includes many subtypes such as patient health record management, seamless connection to other information systems, image viewing support, and proper user authentication and data encryption [4]. The most advanced method in this research area is to use mobile platforms for providing service anywhere and anytime [5].…”

Section: Related Workmentioning

confidence: 99%

Literature Recommendation to Support Clinical Diagnostic Decision — An Approach Based on Link Analysis in the Weighted Keywords Network

Sun¹

2015

IJKE

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Abstract-We present an approach of selecting medical literature for the purpose of supporting clinical diagnostic decision. The proposed approach is based on link analysis in the weighted keywords network. The keywords in the network are extracted from the keywords lists in the articles, the Mesh lexicon and acronyms, with which the full relation of keywords and articles (the link network) is built. In this paper we introduced in details how to extract the collection of valid sentences and diagnosis-related keywords based on the keywords co-occurrence analysis and existing description of symptoms. The paper also lays out the detailed process of measuring the relevance between keywords and articles with link analysis in the weighted keywords network. Finally, we report some related experiments and the results of user evaluations.Index Terms-Clinical decision support, link analysis, weighted keyword network, medical information retrieval.

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Mobile healthcare information management utilizing Cloud Computing and Android OS

Cited by 233 publications

References 8 publications

Cloud Computing and Healthcare Services

Cloud Computing and Healthcare Services

Improving Healthcare Team Collaboration in Hospital Transfers through Cloud-Based Mobile Systems

Literature Recommendation to Support Clinical Diagnostic Decision — An Approach Based on Link Analysis in the Weighted Keywords Network

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