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Cited by 339

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Intelligence in the Internet of Medical Things era: A systematic review of current and future trends

Al-Turjman, Fadi, Nawaz, Muhammad Hassan, Ulusar, Umit Deniz·2020·Computer Communications

Abstract

Abstract Internet of Medical Things (IoMT) envisions a network of medical devices and people, which use wireless communication to enable the exchange of healthcare data. Healthcare costs and prices for services have been increasing with the growing population and the use of advanced technology. The combination of IoMT and healthcare can improve the quality of life, provide better care services and can create more cost-effective systems. This paper introduces the status of IoMT for healthcare industry, including research and development plans and applications. The implementation of the IoMT in healthcare has exponentially increased across the world, but still, it has many technical and design challenges. This paper depicts such challenges and shows a generic IoMT framework that consists of three main components, data acquisition, communication gateways, and servers/cloud, to meet the aforementioned challenges. Finally, this paper discusses the opportunities and prospects of IoMT in practice while emphasizing the corresponding open research issues.

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Crossref · 10.1016/j.comcom.2019.12.030

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Metadata

Authors
Al-Turjman, F., Nawaz, M. H., & Ulusar, U. D.
Venue
Computer Communications
Publisher
Elsevier BV
Published
2020-01
Volume
150
Pages
644-660
ISSN
0140-3664 (ISSN-L)
OpenAlex
W2995573806
Cited by
339
References
54
FWCI
6.87
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Intelligence in the Internet of Medical Things era: A systematic review of current and future trends. https://app.cochat.ai/papers/10.1016/j.comcom.2019.12.030
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Al-Turjman, F., Nawaz, M. H., & Ulusar, U. D. (2020). Intelligence in the Internet of Medical Things era: A systematic review of current and future trends. Computer Communications. https://doi.org/10.1016/j.comcom.2019.12.030

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.