Health Care Equity Through Intelligent Edge Computing and Augmented Reality/Virtual Reality: A Systematic Review

Lakshminarayanan, Vishal; Ravikumar, Aswathy; Sriraman, Harini; Alla, Sujatha; Chattu, Vijay Kumar

doi:10.2147/jmdh.s419923

Cited by 16 publications

(5 citation statements)

References 56 publications

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“…Consequently, the most important data needs to be sent first under traffic. Delays must be minimized, and the highest traffic categories must operate efficiently (Lakshminarayanan et al 2023).…”

Section: Experiments On Prioritizationmentioning

confidence: 99%

Examining medical urgent and patient precedence within the telemedicine landscape with its infrastructure and policies: A comprehensive review

Patel,

Sharma,

Gupta

et al. 2024

Multidiscip. Rev.

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Medical facilities are confronted with grave issues, including a population that is aging and a physician shortage. In an effort to address these issues, telehealth and remote health monitoring systems (RHMS) aim to reduce hospital visits by a small amount. RHMS lessens the workload for primary care patients and enhances inter-unit communication, which lessens the strain on emergency rooms. Due to significant advancements in mobile information transfer and processing of signal technologies, some healthcare researchers have made efforts to employ RHMS in place of hospital visits to provide triage and prioritization for individuals. Prioritization is a strategy for giving people urgent medical care in an attempt to save their lives, while clinical examination determines the severity of a sickness or damage. To emphasize the disadvantages of the present patient screening and prioritization system over the telehealth environment, a crucial inquiry is needed. Based on two crucial axes, an in-depth examination of patient prioritization and medical crisis assessment in a videoconferencing setting was provided in this research. First, a collection, analysis, and classification of earlier research on triage of patients and prioritization in this kind of setting was done. Second, a variety of priorities and standards, as well as various approaches and procedures for prioritization, were provided and examined. The subsequent outcomes were attained: The shortcomings and issues with the current patient prioritization and assessment methods were highlighted. The assessment and priority for individuals who have cardiac conditions were not presented. In the years to come, a structure based on the theory of evidence, as well as the incorporation of a multiple-layer analytical hierarchy approach and method for ranking preference due to resemblance to perfect solutions, can be used to prioritize the care of several patients with ongoing cardiovascular disease by triaging them based on various emergencies dimensions.

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Section: Experiments On Prioritizationmentioning

confidence: 99%

Examining medical urgent and patient precedence within the telemedicine landscape with its infrastructure and policies: A comprehensive review

Patel,

Sharma,

Gupta

et al. 2024

Multidiscip. Rev.

View full text Add to dashboard Cite

show abstract

“…Medium difficulties required more effort but were ultimately resolved. Similarly, integrating cloud solutions such as AWS and Google Cloud [26] - [28] proved overly complex, exceeding the study's scope and the developer's expertise level. Reflecting on the study, the developer acknowledged areas for improvement, particularly in handling cloud computing challenges.…”

Section: Further Improvementsmentioning

confidence: 99%

Enhancing Music Genre Classification through Multi-Algorithm Analysis and User-Friendly Visualization

Navin Kamuni

2024

jes

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The aim of this study is to teach an algorithm how to recognize different types of music. Users will submit songs for analysis. Since the algorithm hasn't heard these songs before, it needs to figure out what makes each song unique. It does this by breaking down the songs into different parts and studying things like rhythm, melody, and tone via supervised learning because the program learns from examples that are already labelled. One important thing to consider when classifying music is its genre, which can be quite complex. To ensure accuracy, we use five different algorithms, each working independently, to analyze the songs. This helps us get a more complete understanding of each song's characteristics. Therefore, our goal is to correctly identify the genre of each submitted song. Once the analysis is done, the results are presented using a graphing tool, making it easy for users to understand and provide feedback.

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“…In preparation for broader 5G integration, this approach represents an important advance in H-IoT. Adding deep learning to SDNs makes H-IoT services, such as telemedicine, more reliable and secure [279]. A softwaredefined network system illustrates the communication process between medical services and nano-networks inside individuals' bodies [280].…”

Section: Software-defined Network (Sdn) In Healthcare-iotmentioning

confidence: 99%

Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation

Khatun,

Memon,

Eising

et al. 2023

IEEE Access

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The Healthcare Internet-of-Things (H-IoT), commonly known as Digital Healthcare, is a datadriven infrastructure that highly relies on smart sensing devices (i.e., blood pressure monitors, temperature sensors, etc.) for faster response time, treatments, and diagnosis. However, with the evolving cyber threat landscape, IoT devices have become more vulnerable to the broader risk surface (e.g., risks associated with generative AI, 5G-IoT, etc.), which, if exploited, may lead to data breaches, unauthorized access, and lack of command and control and potential harm. This paper reviews the fundamentals of healthcare IoT, its privacy, and data security challenges associated with machine learning and H-IoT devices. The paper further emphasizes the importance of monitoring healthcare IoT layers such as perception, network, cloud, and application. Detecting and responding to anomalies involves various cyber-attacks and protocols such as Wi-Fi 6, Narrowband Internet of Things (NB-IoT), Bluetooth, ZigBee, LoRa, and 5G New Radio (5G NR). A robust authentication mechanism based on machine learning and deep learning techniques is required to protect and mitigate H-IoT devices from increasing cybersecurity vulnerabilities. Hence, in this review paper, security and privacy challenges and risk mitigation strategies for building resilience in H-IoT are explored and reported.

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Health Care Equity Through Intelligent Edge Computing and Augmented Reality/Virtual Reality: A Systematic Review

Cited by 16 publications

References 56 publications

Examining medical urgent and patient precedence within the telemedicine landscape with its infrastructure and policies: A comprehensive review

Examining medical urgent and patient precedence within the telemedicine landscape with its infrastructure and policies: A comprehensive review

Enhancing Music Genre Classification through Multi-Algorithm Analysis and User-Friendly Visualization

Machine Learning for Healthcare-IoT Security: A Review and Risk Mitigation

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