B5G-Enabled Distributed Artificial Intelligence on Edges for COVID-19 Pandemic Outbreak Prediction

Hassan, Rafiul; Hassan, Mohammad Mehedi; Altaf, Meteb; Yeasar, Mostafa Shamin; Hossain, Mobarok; Fatema, Kanis; Shaharin, Rubya; Ahmed, Ashraf

doi:10.1109/mnet.011.2000713

Cited by 12 publications

(6 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There are several advantages of using AI to fight against pathogens such as viruses and bacteria that cause a complex reaction in the host [32]. DNN can accelerate the discovery of valuable vaccines or drugs to prevent pandemics and facilitate the diagnosis of diseases [33,34].…”

Section: Discussionmentioning

confidence: 99%

Use of a Deep Learning Approach for the Sensitive Prediction of Hepatitis B Surface Antigen Levels in Inactive Carrier Patients

Kamimura

Nonaka

Mori

et al. 2022

JCM

View full text Add to dashboard Cite

Deep learning is a subset of machine learning that can be employed to accurately predict biological transitions. Eliminating hepatitis B surface antigens (HBsAgs) is the final therapeutic endpoint for chronic hepatitis B. Reliable predictors of the disappearance or reduction in HBsAg levels have not been established. Accurate predictions are vital to successful treatment, and corresponding efforts are ongoing worldwide. Therefore, this study aimed to identify an optimal deep learning model to predict the changes in HBsAg levels in daily clinical practice for inactive carrier patients. We identified patients whose HBsAg levels were evaluated over 10 years. The results of routine liver biochemical function tests, including serum HBsAg levels for 1, 2, 5, and 10 years, and biometric information were obtained. Data of 90 patients were included for adaptive training. The predictive models were built based on algorithms set up by SONY Neural Network Console, and their accuracy was compared using statistical analysis. Multiple regression analysis revealed a mean absolute percentage error of 58%, and deep learning revealed a mean absolute percentage error of 15%; thus, deep learning is an accurate predictive discriminant tool. This study demonstrated the potential of deep learning algorithms to predict clinical outcomes.

show abstract

Section: Discussionmentioning

confidence: 99%

Use of a Deep Learning Approach for the Sensitive Prediction of Hepatitis B Surface Antigen Levels in Inactive Carrier Patients

Kamimura

Nonaka

Mori

et al. 2022

JCM

View full text Add to dashboard Cite

show abstract

“…From the above, it can be seen that AI is effectively used in various aspects of COVID-19 countermeasures. Due to space limitations, we were unable to describe them in this review, but notable contributions have also been made through the use of distributed artificial intelligence and agent-based models [138][139][140]. We note that, from the perspective of preventing infectious diseases, it is necessary to reduce human contact and unnecessary human flow, which is why information and communication technology in social life is advancing worldwide [141][142][143].…”

Section: Discussionmentioning

confidence: 99%

Application of Artificial Intelligence in COVID-19 Diagnosis and Therapeutics

Asada

Komatsu

Shimoyama

et al. 2021

JPM

View full text Add to dashboard Cite

The coronavirus disease 2019 (COVID-19) pandemic began at the end of December 2019, giving rise to a high rate of infections and causing COVID-19-associated deaths worldwide. It was first reported in Wuhan, China, and since then, not only global leaders, organizations, and pharmaceutical/biotech companies, but also researchers, have directed their efforts toward overcoming this threat. The use of artificial intelligence (AI) has recently surged internationally and has been applied to diverse aspects of many problems. The benefits of using AI are now widely accepted, and many studies have shown great success in medical research on tasks, such as the classification, detection, and prediction of disease, or even patient outcome. In fact, AI technology has been actively employed in various ways in COVID-19 research, and several clinical applications of AI-equipped medical devices for the diagnosis of COVID-19 have already been reported. Hence, in this review, we summarize the latest studies that focus on medical imaging analysis, drug discovery, and therapeutics such as vaccine development and public health decision-making using AI. This survey clarifies the advantages of using AI in the fight against COVID-19 and provides future directions for tackling the COVID-19 pandemic using AI techniques.

show abstract

“…Healthcare [22] [23] [24]. Building new intelligent and efficient frameworks is becoming easier with the features pro-vided by B5G, such as low latency, larger area coverage, higher data rate, and real-time communication [25]. Similarly, social media is a potentially good platform for disseminating important information during the pandemic [26].…”

Section: Cluster 1: Technologymentioning

confidence: 99%

Research Progress of Digital Technology and Emerging Themes During Covid 19 in Malaysia: Bibliometric Analysis Approach

Kiflee

Hasbullah

Ahmad

et al. 2023

Int. J. Interact. Mob. Technol.

View full text Add to dashboard Cite

The covid 19 immediate impact has intensely changed global trends. At the same time, the impact covid 19 has exhilarated research interest among researchers worldwide. In Malaysia, the Movement Control Order (MCO) and travel restrictions enforced by the Malaysian Government in March 2020 have significantly hit Malaysian daily life. Therefore, understanding the topic of interest and broadening collaboration networks is critically important to advance research development. This bibliometric study examines the Covid-19 research trends in Malaysia based on publication output, affiliated countries, and author co-occurrences. Utilizing the Scopus database, 1776 articles were identified and extracted from 2020 until 2021. The result has shown that the number of articles related to Covid 19 in Malaysia significantly increased in 2021, resulting in higher cumulative total publications. Most Covid 19 research publications in Malaysia collaborated with the United Kingdom, Pakistan, and United States. The bibliometric literature in this study have declared that digital technologies have the potential to fulfill customized requirements of COVID-19 pandemic. Thinking about advance technologies and its benefits, this study is going to provide a through literature about the application of advance technologies in real-time. Despite of that, this study also mapped the literature based on topic of interest to understand the benefits and application of these technologies in different areas including pure technology, sustainability, education, tourism, psychology, food and agriculture, and the economy.

show abstract

B5G-Enabled Distributed Artificial Intelligence on Edges for COVID-19 Pandemic Outbreak Prediction

Cited by 12 publications

References 13 publications

Use of a Deep Learning Approach for the Sensitive Prediction of Hepatitis B Surface Antigen Levels in Inactive Carrier Patients

Use of a Deep Learning Approach for the Sensitive Prediction of Hepatitis B Surface Antigen Levels in Inactive Carrier Patients

Application of Artificial Intelligence in COVID-19 Diagnosis and Therapeutics

Research Progress of Digital Technology and Emerging Themes During Covid 19 in Malaysia: Bibliometric Analysis Approach

Contact Info

Product

Resources

About