AdapteR Interoperability ENgine (ARIEN): An approach of Interoperable CDSS for Ubiquitous Healthcare

Khan, Wajahat Ali; Hussain, Maqbool; Amin, Bilal; Khattak, Asad Masood; Afzal, Muhammad; Lee, Sungyoung

doi:10.1007/978-3-319-03176-7_32

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…In the past few years, several projects, studies, ontologies and systems have been developed to empower healthcare processes and interoperability by means of semantic technologies (Dogac et al, 2006;Gene Ontology Consortium, 2016;SNOMED CT, 2016;Unified Medical Language System, 2016;Hein et al, 2006;Khan et al, 2013).…”

Section: Semantic Opportunities and Positive Consequencesmentioning

confidence: 99%

Fog computing architectures for healthcare

Prieto-González

Jaedicke

Schubert

et al. 2016

JICES

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Purpose The purpose of this study is to analyze how embedding of self-powered wireless sensors into cloud computing further enables such a system to become a sustainable part of work environment. Design/methodology/approach This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT project in Germany. A clearly outlined three-layer architecture, in the sense of Internet of Things, is presented. It provides the basis for integrating a broad range of sensors into smart healthcare infrastructure. More specifically, by making use of short-range communication sensors (sensing layer), gateways which implement data transmission and low-level computation (fog layer) and cloud computing for processing the data (application layer). Findings A technical in-depth analysis of the first two layers of the infrastructure is given to prove reliability and to determine the communication quality and availability in real-world scenarios. Furthermore, two example use-cases that directly apply to a healthcare environment are examined, concluding with the feasibility of the presented approach. Practical implications Finally, the next research steps, oriented towards the semantic tagging and classification of data received from sensors, and the usage of advanced artificial intelligence-based algorithms on this information to produce useful knowledge, are described together with the derived social benefits. Originality/value The work presents an innovative, extensible and scalable system, proven to be useful in healthcare environments.

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Section: Semantic Opportunities and Positive Consequencesmentioning

confidence: 99%

Fog computing architectures for healthcare

Prieto-González

Jaedicke

Schubert

et al. 2016

JICES

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“…The patient's data are obtained from the EMR system in HL7 CDA format and are converted to HL7 vMR format for integration with our proposed system. 16 The patient can perform activities that require a response by decision support based on medication. This decision requires physician consultation; therefore the medication that the decision support system finds out is communicated with the EMR system in the form of an alert to the physician.…”

Section: Integration With Emr Systemmentioning

confidence: 99%

“…Moreover, it also supports Adapter Interoperability and Adapter EMR/EHR, which enable data and recommendation exchanges with clinical systems. 16 The proposed system has a greater impact for the healthcare community. Patients are provided with healthcare services by processing sensor data collected related to them.…”

Section: Introductionmentioning

confidence: 99%

Recommendations Service for Chronic Disease Patient in Multimodel Sensors Home Environment

Hussain

Ali²,

Khan³

et al. 2015

Telemedicine and e-Health

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With advanced technologies in hand, there exist potential applications and services built around monitoring activities of daily living (ADL) of elderly people at nursing homes. Most of the elderly people in these facilities are suffering from different chronic diseases such as dementia. Existing technologies are mainly focusing on non-medication interventions and monitoring of ADL for addressing loss of autonomy or well-being. Monitoring and managing ADL related to cognitive behaviors for non-medication intervention are very effective in improving dementia patients' conditions. However, cognitive functions of patients can be improved if appropriate recommendations of medications are delivered at a particular time. Previously we developed the Secured Wireless Sensor Network Integrated Cloud Computing for Ubiquitous-Life Care (SC 3

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