Paradigm of IoT big data analytics in the healthcare industry: A review of scientific literature and mapping of research trends

Saheb, Tahereh; Izadi, Leila

doi:10.1016/j.tele.2019.03.005

Cited by 152 publications

(65 citation statements)

References 33 publications

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“…Malik, Abdallah, and Ala'raj (2018) reviewed the use of BDA in supply chain management in healthcare. Saheb and Izadi (2019) reviewed the use of big data sourced from Internet-of-Things devices in the healthcare industry. Such review studies are not designed to provide a comprehensive review of the literature on BDA in healthcare.…”

Section: Introductionmentioning

confidence: 99%

Big data analytics in healthcare: a systematic literature review

Khanra

Dhir

Islam

et al. 2020

Enterprise Information Systems

174

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The current study performs a systematic literature review (SLR) to synthesise prior research on the applicability of big data analytics (BDA) in healthcare. The SLR examines the outcomes of 41 studies, and presents them in a comprehensive framework. The findings from this study suggest that applications of BDA in healthcare can be observed from five perspectives, namely, health awareness among the general public, interactions among stakeholders in the healthcare ecosystem, hospital management practices, treatment of specific medical conditions, and technology in healthcare service delivery. This SLR recommends actionable future research agendas for scholars and valuable implications for theory and practice.

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Section: Introductionmentioning

confidence: 99%

Big data analytics in healthcare: a systematic literature review

Khanra

Dhir

Islam

et al. 2020

Enterprise Information Systems

174

View full text Add to dashboard Cite

show abstract

“…In recent years, smart, innovative frameworks have emerged, fusing IoT and big data analytics for the healthcare industry ( Saheb et al., 2019 ). ML and big data mining have already been used in the past for disease prediction and analysis ( Dimitrov, 2016 ; Hameed et al., 2017 ; Vinitha et al., 2018 ).…”

Section: Artificial Intelligence and Big Data Technology In Iomtmentioning

confidence: 99%

“… Reference Scope Predictive Model Data Mining & Analytics Decision Making Systematic Classification Dimitrov (2016) Healthcare domain Yes Yes Vinitha et al. (2018) Disease domain Yes Yes Saheeb et al., 2019 Healthcare domain Yes Yes Cascella et al. (2020) COVID-19 disease domain Yes Yes Jia et al.…”

Section: Artificial Intelligence and Big Data Technology In Iomtmentioning

confidence: 99%

IoMT amid COVID-19 pandemic: Application, architecture, technology, and security

Aman

Hassan

Sameen

et al. 2021

Journal of Network and Computer Applications

146

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In many countries, the Internet of Medical Things (IoMT) has been deployed in tandem with other strategies to curb the spread of COVID-19, improve the safety of front-line personnel, increase efficacy by lessening the severity of the disease on human lives, and decrease mortality rates. Significant inroads have been achieved in terms of applications and technology, as well as security which have also been magnified through the rapid and widespread adoption of IoMT across the globe. A number of on-going researches show the adoption of secure IoMT applications is possible by incorporating security measures with the technology. Furthermore, the development of new IoMT technologies merge with Artificial Intelligence, Big Data and Blockchain offers more viable solutions. Hence, this paper highlights the IoMT architecture, applications, technologies, and security developments that have been made with respect to IoMT in combating COVID-19. Additionally, this paper provides useful insights into specific IoMT architecture models, emerging IoMT applications, IoMT security measurements, and technology direction that apply to many IoMT systems within the medical environment to combat COVID-19.

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“…Imaging informatics is the study of methods for generating, managing, and representing imaging information in various biomedical applications. It is concerned with how medical images are exchanged and analysed throughout complex healthcare systems [115,116]. e authors of the study [117] introduce a novel telemammography system for early detection of breast cancer with the help of image processing and machine learning techniques.…”

Section: Scientific Programmingmentioning

confidence: 99%

A Systematic Review of Healthcare Big Data

Raja

Mukherjee

Sarkar

2020

Scientific Programming

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Over the past decade, data recorded (due to digitization) in healthcare sectors have continued to increase, intriguing the thought about big data in healthcare. There already exists plenty of information, ready for analysis. Researchers are always putting their best effort to find valuable insight from the healthcare big data for quality medical services. This article provides a systematic review study on healthcare big data based on the systematic literature review (SLR) protocol. In particular, the present study highlights some valuable research aspects on healthcare big data, evaluating 34 journal articles (between 2015 and 2019) according to the defined inclusion-exclusion criteria. More specifically, the present study focuses to determine the extent of healthcare big data analytics together with its applications and challenges in healthcare adoption. Besides, the article discusses big data produced by these healthcare systems, big data characteristics, and various issues in dealing with big data, as well as how big data analytics contributes to achieve a meaningful insight on these data set. In short, the article summarizes the existing literature based on healthcare big data, and it also helps the researchers with a foundation for future study in healthcare contexts.

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Paradigm of IoT big data analytics in the healthcare industry: A review of scientific literature and mapping of research trends

Cited by 152 publications

References 33 publications

Big data analytics in healthcare: a systematic literature review

Big data analytics in healthcare: a systematic literature review

IoMT amid COVID-19 pandemic: Application, architecture, technology, and security

A Systematic Review of Healthcare Big Data

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