An empirical investigation into the altering health perspectives in the internet of health things

Bahbouh, Nour Mahmoud; Compte, Sandra Sendra; Valdes, Juan Valenzuela; Sen, Adnan Ahmed Abi

doi:10.1007/s41870-022-01035-3

Cited by 15 publications

(5 citation statements)

References 105 publications

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“…Privacy and security are issues of primary importance in the Healthcare sector, where it is mandatory the protect the patient data from malicious disclosure. It has been pointed out that so far this issue is largely an open challenge (Bahbouh et al, 2023). It is worth noting that signals in this direction come from the basic research side (Jang et al, 2021;Pal et al, 2023).…”

Section:  Programming Thingsboard Offers a Rich Package Ofmentioning

confidence: 99%

Papers Mentioning Things Board: A Systematic Mapping Study

Di Felice,

Paolone

2024

Journal of Computer Science

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In a previous article, we conducted a Systematic Mapping Study (SMS) devoted to identifying the open-source IoT platform that nowadays offers the most features as well as adequate documentation and which, therefore, is a useful middleware in the development of IoT applications. In light of the final findings of such a study, ThingsBoard was selected. The present paper reports on the findings of a subsequent mapping study. We queried the Scopus database looking for articles that mention ThingsBoard either in the Title, in the Abstract, or among the authors' Keywords. 55 items were retrieved and carefully read. At the end of this stage, we were able to answer the following research questions: Are there available studies mentioning ThingsBoard? In which ambits? What is the role of ThingsBoard in the studies where it is mentioned? What are the gaps in current research and the implications for future research? The study goals are general, so the final findings might be of interest to IoT professionals, as well as to scholars. In detail, the SMS provides insights into the breadth of usage and the domains where ThingsBoard has been applied successfully, indicating its suitability and potential for a wide range of IoT-related projects. Moreover, a few gaps to be filled with further research have emerged.

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Section:  Programming Thingsboard Offers a Rich Package Ofmentioning

confidence: 99%

Papers Mentioning Things Board: A Systematic Mapping Study

Di Felice,

Paolone

2024

Journal of Computer Science

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“…In addition, the dependence on imagery data sourced from a single site or imaging modality may lead the model to overfit explicit data distributions, impeding its capacity to generalize to unseen data and varied clinical situations. This inherent bias brings a major limit to the generalization performance of ML in healthcare systems [ 8 – 10 ]. Hence, overlooking this bias usually makes the ML model operate in a suboptimal way, thereby reducing the reliability of related diagnostic decisions, and making ML non-applicable in real-world clinical environments.…”

Section: Introductionmentioning

confidence: 99%

Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies

Alrashdi

2024

BMC Med Imaging

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The quick proliferation of pandemic diseases has been imposing many concerns on the international health infrastructure. To combat pandemic diseases in smart cities, Artificial Intelligence of Things (AIoT) technology, based on the integration of artificial intelligence (AI) with the Internet of Things (IoT), is commonly used to promote efficient control and diagnosis during the outbreak, thereby minimizing possible losses. However, the presence of multi-source institutional data remains one of the major challenges hindering the practical usage of AIoT solutions for pandemic disease diagnosis. This paper presents a novel framework that utilizes multi-site data fusion to boost the accurateness of pandemic disease diagnosis. In particular, we focus on a case study of COVID-19 lesion segmentation, a crucial task for understanding disease progression and optimizing treatment strategies. In this study, we propose a novel multi-decoder segmentation network for efficient segmentation of infections from cross-domain CT scans in smart cities. The multi-decoder segmentation network leverages data from heterogeneous domains and utilizes strong learning representations to accurately segment infections. Performance evaluation of the multi-decoder segmentation network was conducted on three publicly accessible datasets, demonstrating robust results with an average dice score of 89.9% and an average surface dice of 86.87%. To address scalability and latency issues associated with centralized cloud systems, fog computing (FC) emerges as a viable solution. FC brings resources closer to the operator, offering low latency and energy-efficient data management and processing. In this context, we propose a unique FC technique called PANDFOG to deploy the multi-decoder segmentation network on edge nodes for practical and clinical applications of automated COVID-19 pneumonia analysis. The results of this study highlight the efficacy of the multi-decoder segmentation network in accurately segmenting infections from cross-domain CT scans. Moreover, the proposed PANDFOG system demonstrates the practical deployment of the multi-decoder segmentation network on edge nodes, providing real-time access to COVID-19 segmentation findings for improved patient monitoring and clinical decision-making.

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“…The Internet of Health Things could be a holder for all the past concepts. It has other modern highlights such as mindfulness, shrewd restorative gadgets, robots, and telehealth, as well as the advancement of restorative instruction utilizing virtual reality methods, holographic tangible communication, and 3D imaging for a way better conclusion of the illness (10).…”

Section: Introductionmentioning

confidence: 99%

The Application of Internet of Things in Healthcare Systems with a Focus on Advantages and Challenges: A Scoping Review

Pahlevanynejad,

Hosseini,

Salmani

et al. 2023

J Educ Community Health

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Background: The internet of things (IoT) has become a heterogeneous and exceedingly disseminated structure that can react to the everyday needs of individuals and distinctive organizations. The present study aimed to investigate the application of the IoT in healthcare systems, with a focus on its strengths and challenges. Methods: Electronic databases, including PubMed, Scopus, SID, and Magiran, were searched for this review study. In addition, a review of the gray literature was undertaken to identify relevant studies in English on the current subject. The titles, abstracts, and full texts were independently screened based on PRISMA guidelines for the scoping literature. General information containing the author(s) name, year of publication, the aim of the study, and specific information, including technologies used in IoT, the medical field, the application of IoT in health, limitations, and strengths, were extracted and analyzed. Results: Forty-four papers were qualified and contained in the process to 2023. Different studies have mentioned the opportunities for different forms of IoT applications, such as remote consultation, health monitoring and care, medication management, quick diagnosis, and effective treatment. In addition, studies have addressed the challenges in different forms, such as remembering everyday events, fitness, remote rehabilitation, management of chronic diseases, E-Visit, and better management of daily activities. Conclusion: The challenges and the benefits were classified into nine and ten main groups, respectively. Each of these challenges and benefits, which include smaller and more current elements, can help health policymakers apply the IoT and use its benefits.

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An empirical investigation into the altering health perspectives in the internet of health things

Cited by 15 publications

References 105 publications

Papers Mentioning Things Board: A Systematic Mapping Study

Papers Mentioning Things Board: A Systematic Mapping Study

Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies

The Application of Internet of Things in Healthcare Systems with a Focus on Advantages and Challenges: A Scoping Review

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