AIMC Topic: SARS-CoV-2

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Designing Supportive Dashboards for Crisis Response to Protect Vulnerable Populations: A Qualitative Study.

Studies in health technology and informatics
INTRODUCTION: The COVID-19 pandemic exposed both direct and collateral health impacts especially on vulnerable populations, underscoring the need for more targeted and equitable crisis response strategies. Health-related dashboards could support bett...

Machine learning insights on the effectiveness of non-pharmaceutical interventions against COVID-19 in Nigeria.

International health
BACKGROUND: The lack of effective pharmacological measures during the early phase of the COVID-19 pandemic prompted the implementation of non-pharmaceutical interventions (NPIs) as initial mitigation strategies. The impact of these NPIs on COVID-19 i...

Bridging sustainable finance, AI, and clean technology amid economic shocks: How are they connected in median and extreme conditions?

Journal of environmental management
We investigate the intricate relationships between sustainable markets, artificial intelligence (AI), and clean technology, focusing on their contributions to investment and risk management. Employing the Quantile-on-Quantile (QQ) connectedness frame...

Lyophilized nasal swabs for COVID-19 detection by ATR-FTIR spectroscopy: Machine learning-based approach.

Biophysical chemistry
The COVID-19 pandemic continues to pose challenges for global health. The disease burden and diagnostic pressure has forced scientists to explore alternate diagnostic tools beyond the standard PCR testing. One such promising tool is the use of spectr...

A Neural Embedding Approach to Mapping Health Concepts to Concept Unique Identifiers.

Studies in health technology and informatics
Understanding health concepts in free text is an important task in biomedical NLP. Being able to map the extracted concepts to unique concept identifiers can facilitate integration of and interoperability across biomedical informatics applications. A...

A review: Lightweight architecture model in deep learning approach for lung disease identification.

Computers in biology and medicine
As one of the leading causes of death worldwide, early detection of lung disease is a very important step to improve the effectiveness of treatment. By using medical image data, such as X-ray or CT-scan, classification of lung disease can be done. De...

Investigating the interpretability of ChatGPT in mental health counseling: An analysis of artificial intelligence generated content differentiation.

Computer methods and programs in biomedicine
The global impact of COVID-19 has caused a significant rise in the demand for psychological counseling services, creating pressure on existing mental health professionals. Large language models (LLM), like ChatGPT, are considered a novel solution for...

SARS-CoV-2: lessons in virus mutation prediction and pandemic preparedness.

Current opinion in immunology
The COVID-19 pandemic has prompted an unprecedented global response. In particular, extraordinary efforts have been dedicated toward monitoring and predicting variant emergence due to its huge impact, particularly for vaccine escape. Broadly, we clas...

Precision Symptom Phenotyping Identifies Early Clinical and Proteomic Predictors of Distinct COVID-19 Sequelae.

The Journal of infectious diseases
BACKGROUND: Post-COVID conditions (PCC) are difficult to characterize, diagnose, predict, and treat due to overlapping symptoms and poorly understood pathology. Identifying inflammatory profiles may improve clinical prognostication and trial endpoint...

A Transformer-Based Framework for Counterfactual Estimation of Antihypertensive Treatment Effect on COVID-19 Infection Risk - A Proof-of-Concept Study.

American journal of hypertension
BACKGROUND: Transformer-based neural networks excel in modelling high-dimensional, time-series data with complex dependencies. This proof-of-concept study applies a transformer-X-learner framework to estimate treatment effects using real-world data, ...