2,111 research outputs found

    How 5G wireless (and concomitant technologies) will revolutionize healthcare?

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    The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution

    Towards the Use of Big Data in Healthcare: a literature review

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    The interest in new and more advanced technological solutions is paving the way for the diffusion of innovative and revolutionary applications in healthcare organizations. The application of an artificial intelligence system to medical research has the potential to move toward highly advanced e-Health. This analysis aims to explore the main areas of application of big data in healthcare, as well as the restructuring of the technological infrastructure and the integration of traditional data analytical tools and techniques with an elaborate computational technology that is able to enhance and extract useful information for decision-making. We conducted a literature review using the Scopus database over the period 2010-2020. The article selection process involved five steps: the planning and identification of studies, the evaluation of articles, the extraction of results, the summary, and the dissemination of the audit results. We included 93 documents. Our results suggest that effective and patient-centered care cannot disregard the acquisition, management, and analysis of a huge volume and variety of health data. In this way, an immediate and more effective diagnosis could be possible while maximizing healthcare resources. Deriving the benefits associated with digitization and technological innovation, however, requires the restructuring of traditional operational and strategic processes, and the acquisition of new skills

    Big data architecture for pervasive healthcare: a literature review

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    Pervasive healthcare aims to deliver deinstitutionalised healthcare services to patients anytime and anywhere. Pervasive healthcare involves remote data collection through mobile devices and sensor network which the data is usually in large volume, varied formats and high frequency. The nature of big data such as volume, variety, velocity and veracity, together with its analytical capabilities com-plements the delivery of pervasive healthcare. However, there is limited research in intertwining these two domains. Most research focus mainly on the technical context of big data application in the healthcare sector. Little attention has been paid to a strategic role of big data which impacts the quality of healthcare services provision at the organisational level. Therefore, this paper delivers a conceptual view of big data architecture for pervasive healthcare via an intensive literature review to address the aforementioned research problems. This paper provides three major contributions: 1) identifies the research themes of big data and pervasive healthcare, 2) establishes the relationship between research themes, which later composes the big data architecture for pervasive healthcare, and 3) sheds a light on future research, such as semiosis and sense-making, and enables practitioners to implement big data in the pervasive healthcare through the proposed architecture

    Telehealth innovation:Current directions and future opportunities

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