AIMC Topic: Pandemics

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An adaptive data-driven architecture for mental health care applications.

PeerJ
BACKGROUND: In the current era of rapid technological innovation, our lives are becoming more closely intertwined with digital systems. Consequently, every human action generates a valuable repository of digital data. In this context, data-driven arc...

Deep learning in public health: Comparative predictive models for COVID-19 case forecasting.

PloS one
The COVID-19 pandemic has had a significant impact on both the United Arab Emirates (UAE) and Malaysia, emphasizing the importance of developing accurate and reliable forecasting mechanisms to guide public health responses and policies. In this study...

Charting the future of patient care: A strategic leadership guide to harnessing the potential of artificial intelligence.

Healthcare management forum
Artificial Intelligence (AI) applications have the potential to revolutionize conventional healthcare practices, creating a more efficient and patient-centred approach with improved outcomes. This guide discuses eighteen AI-based applications in clin...

Algorithmic and sensor-based research on Chinese children's and adolescents' screen use behavior and light environment.

Frontiers in public health
BACKGROUND: Myopia poses a global health concern and is influenced by both genetic and environmental factors. The incidence of myopia tends to increase during infectious outbreaks, such as the COVID-19 pandemic. This study examined the screen-time be...

DeepCSFusion: Deep Compressive Sensing Fusion for Efficient COVID-19 Classification.

Journal of imaging informatics in medicine
Worldwide, the COVID-19 epidemic, which started in 2019, has resulted in millions of deaths. The medical research community has widely used computer analysis of medical data during the pandemic, specifically deep learning models. Deploying models on ...

Transforming drug development with synthetic biology and AI.

Trends in biotechnology
The COVID-19 pandemic has thrust RNA as a platform for drug development into the spotlight. However, identifying promising drug candidates is challenging. With advances in synthetic biology and artificial intelligence (AI) models, we can overcome thi...

Machine learning-based prediction of vitamin D deficiency: NHANES 2001-2018.

Frontiers in endocrinology
BACKGROUND: Vitamin D deficiency is strongly associated with the development of several diseases. In the current context of a global pandemic of vitamin D deficiency, it is critical to identify people at high risk of vitamin D deficiency. There are n...

Coordinating virus research: The Virus Infectious Disease Ontology.

PloS one
The COVID-19 pandemic prompted immense work on the investigation of the SARS-CoV-2 virus. Rapid, accurate, and consistent interpretation of generated data is thereby of fundamental concern. Ontologies-structured, controlled, vocabularies-are designed...

Agent-based social simulations for health crises response: utilising the everyday digital health perspective.

Frontiers in public health
There is increasing recognition of the role that artificial intelligence (AI) systems can play in managing health crises. One such approach, which allows for analysing the potential consequences of different policy interventions is agent-based social...

Natural Language Processing for Smart Healthcare.

IEEE reviews in biomedical engineering
Smart healthcare has achieved significant progress in recent years. Emerging artificial intelligence (AI) technologies enable various smart applications across various healthcare scenarios. As an essential technology powered by AI, natural language p...