IoMT Platform for Pervasive Healthcare Data Aggregation, Processing, and Sharing Based on OneM2M and OpenEHR.
TLDR
An Internet of Medical Things (IoMT) platform for pervasive healthcare that ensures interoperability, quality of the detection process, and scalability in an M2M-based architecture, and provides functionalities for the processing of high volumes of data, knowledge extraction, and common healthcare services is proposed.Abstract:
Pervasive healthcare services have undergone a great evolution in recent years. The technological development of communication networks, including the Internet, sensor networks, and M2M (Machine-to-Machine) have given rise to new architectures, applications, and standards related to addressing almost all current e-health challenges. Among the standards, the importance of OpenEHR has been recognized, since it enables the separation of medical semantics from data representation of electronic health records. However, it does not meet the requirements related to interoperability of e-health devices in M2M networks, or in the Internet of Things (IoT) scenarios. Moreover, the lack of interoperability hampers the application of new data-processing techniques, such as data mining and online analytical processing, due to the heterogeneity of the data and the sources. This article proposes an Internet of Medical Things (IoMT) platform for pervasive healthcare that ensures interoperability, quality of the detection process, and scalability in an M2M-based architecture, and provides functionalities for the processing of high volumes of data, knowledge extraction, and common healthcare services. The platform uses the semantics described in OpenEHR for both data quality evaluation and standardization of healthcare data stored by the association of IoMT devices and observations defined in OpenEHR. Moreover, it enables the application of big data techniques and online analytic processing (OLAP) through Hadoop Map/Reduce and content-sharing through fast healthcare interoperability resource (FHIR) application programming interfaces (APIs).read more
Citations
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References
More filters
Journal ArticleDOI
Scalable and accurate deep learning with electronic health records
Alvin Rajkomar,Alvin Rajkomar,Eyal Oren,Kai Chen,Andrew M. Dai,Nissan Hajaj,Michaela Hardt,Peter J. Liu,Xiaobing Liu,Jake Marcus,Mimi Sun,Patrik Sundberg,Hector Yee,Kun Zhang,Yi Zhang,Gerardo Flores,Gavin E. Duggan,Jamie Irvine,Quoc V. Le,Kurt Litsch,Alexander Mossin,Justin Tansuwan,De Wang,James Wexler,Jimbo Wilson,Dana Ludwig,Samuel L. Volchenboum,Katherine Chou,Michael Pearson,Srinivasan Madabushi,Nigam H. Shah,Atul J. Butte,Michael D. Howell,Claire Cui,Greg S. Corrado,Jeffrey Dean +35 more
TL;DR: A representation of patients’ entire raw EHR records based on the Fast Healthcare Interoperability Resources (FHIR) format is proposed, and it is demonstrated that deep learning methods using this representation are capable of accurately predicting multiple medical events from multiple centers without site-specific data harmonization.
Journal ArticleDOI
Scalable and accurate deep learning for electronic health records
Alvin Rajkomar,Eyal Oren,Kai Chen,Andrew M. Dai,Nissan Hajaj,Peter J. Liu,Xiaobing Liu,Mimi Sun,Patrik Sundberg,Hector Yee,Kun Zhang,Gavin E. Duggan,Gerardo Flores,Michaela Hardt,Jamie Irvine,Quoc V. Le,Kurt Litsch,Jake Marcus,Alexander Mossin,Justin Tansuwan,De Wang,James Wexler,Jimbo Wilson,Dana Ludwig,Samuel L. Volchenboum,Katherine Chou,Michael Pearson,Srinivasan Madabushi,Nigam H. Shah,Atul J. Butte,Michael D. Howell,Claire Cui,Greg S. Corrado,Jeffrey Dean +33 more
TL;DR: In this paper, the authors proposed a representation of patients' entire, raw EHR records based on the Fast Healthcare Interoperability Resources (FHIR) format and demonstrated that deep learning methods using this representation are capable of accurately predicting multiple medical events from multiple centers without site-specific data harmonization.
Journal ArticleDOI
SMART on FHIR: a standards-based, interoperable apps platform for electronic health records
Joshua C. Mandel,Joshua C. Mandel,David A. Kreda,Kenneth D. Mandl,Isaac S. Kohane,Rachel B. Ramoni +5 more
TL;DR: The SMART on FHIR ( Substitutable Medical Applications and Reusable Technologies) platform as discussed by the authors is based on the Fast Health Interoperability Resources (FHIR) standard.
Proceedings ArticleDOI
Choice of effective messaging protocols for IoT systems: MQTT, CoAP, AMQP and HTTP
TL;DR: An evaluation of the four established messaging protocols MQTT, CoAP, AMQP and HTTP for IoT systems is presented and the user can decide their appropriate usage in various IoT systems according to their requirements and suitability.
Proceedings ArticleDOI
HL7 FHIR: An Agile and RESTful approach to healthcare information exchange
Duane Bender,Kamran Sartipi +1 more
TL;DR: This research examines the potential for new Health Level 7 (HL7) standard Fast Healthcare Interoperability Resources (FHIR, pronounced “fire”) standard to help achieve healthcare systems interoperability.