Perceptions of registered nurses on facilitators and barriers of implementing the AI-IoT-based healthcare pilot project for older adults during the COVID-19 pandemic in South Korea

Boo, Sunjoo; Oh, Hyunjin

doi:10.3389/fpubh.2023.1234626

Cited by 3 publications

References 29 publications

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The Role of Artificial Intelligence in Modern Medical Education and Practice: A Systematic Literature Review

Rasouli,

Alkurdi,

Jia

2024

Preprint

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The integration of Artificial Intelligence (AI) into medical education has emerged as a transformative element in the modern healthcare educational system. With the exponential growth of medical knowledge and the increasing complexity of healthcare systems, AI offers innovative solutions to enhance learning outcomes, facilitate personalized education pathways, and improve clinical decision-making skills among medical professionals. This literature review explores the transformative role of AI in the training of healthcare providers, focusing on advancements in medical education, medical diagnostics, and emergency care training. Additionally, it addresses the readiness of healthcare professionals to employ AI technologies, analyzing their current knowledge, attitudes, and the training provided. By synthesizing findings from multiple studies, we aim to highlight AI's potential to enhance medical education, address challenges, and propose future directions for integrating AI into healthcare training.

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The Role of Artificial Intelligence in Modern Medical Education and Practice: A Systematic Literature Review

Rasouli,

Alkurdi,

Jia

2024

Preprint

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The digital transformation of nursing practice: an analysis of advanced IoT technologies and smart nursing systems

Wang,

Shi,

Han

et al. 2024

Front. Med.

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Facing unprecedented challenges due to global population aging and the prevalence of chronic diseases, the healthcare sector is increasingly relying on innovative solutions. Internet of Things (IoT) technology, by integrating sensing, network communication, data processing, and security technologies, offers promising approaches to address issues such as nursing personnel shortages and rising healthcare costs. This paper reviews the current state of IoT applications in healthcare, including key technologies, frameworks for smart nursing platforms, and case studies. Findings indicate that IoT significantly enhances the efficiency and quality of care, particularly in real-time health monitoring, disease management, and remote patient supervision. However, challenges related to data quality, user acceptance, and economic viability also arise. Future trends in IoT development will likely focus on increased intelligence, precision, and personalization, while international cooperation and policy support are critical for the global adoption of IoT in healthcare. This review provides valuable insights for policymakers, researchers, and practitioners in healthcare and suggests directions for future research and technological advancements.

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Enabling Pandemic-Resilient Healthcare: Edge-Computing-Assisted Real-Time Elderly Caring Monitoring System

Islam,

Sagar,

Kim

2024

Applied Sciences

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Over the past few years, life expectancy has increased significantly. However, elderly individuals living independently often require assistance due to mobility issues, symptoms of dementia, or other health-related challenges. In these situations, high-quality elderly care systems for the aging population require innovative approaches to guarantee Quality of Service (QoS) and Quality of Experience (QoE). Traditional remote elderly care methods face several challenges, including high latency and poor service quality, which affect their transparency and stability. This paper proposes an Edge Computational Intelligence (ECI)-based haptic-driven ECI-TeleCaring system for the remote caring and monitoring of elderly people. It utilizes a Software-Defined Network (SDN) and Mobile Edge Computing (MEC) to reduce latency and enhance responsiveness. Dual Long Short-Term Memory (LSTM) models are deployed at the edge to enable real-time location-aware activity prediction to ensure QoS and QoE. The results from the simulation demonstrate that the proposed system is proficient in managing the transmission of data in real time without and with an activity recognition and location-aware model by communication latency under 2.5 ms (more than 60%) and from 11∼12 ms (60∼95%) for 10 to 1000 data packets, respectively. The results also show that the proposed system ensures a trade-off between the transparency and stability of the system from the QoS and QoE perspectives. Moreover, the proposed system serves as a testbed for implementing, investigating, and managing elder telecaring services for QoS/QoE provisioning. It facilitates real-time monitoring of the deployed technological parameters along with network delay and packet loss, and it oversees data exchange between the master domain (human operator) and slave domain (telerobot).

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Perceptions of registered nurses on facilitators and barriers of implementing the AI-IoT-based healthcare pilot project for older adults during the COVID-19 pandemic in South Korea

Cited by 3 publications

References 29 publications

The Role of Artificial Intelligence in Modern Medical Education and Practice: A Systematic Literature Review

The Role of Artificial Intelligence in Modern Medical Education and Practice: A Systematic Literature Review

The digital transformation of nursing practice: an analysis of advanced IoT technologies and smart nursing systems

Enabling Pandemic-Resilient Healthcare: Edge-Computing-Assisted Real-Time Elderly Caring Monitoring System

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