AIMC Topic: COVID-19

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Era of Generalist Conversational Artificial Intelligence to Support Public Health Communications.

Journal of medical Internet research
The integration of artificial intelligence (AI) into health communication systems has introduced a transformative approach to public health management, particularly during public health emergencies, capable of reaching billions through familiar digit...

An effective COVID-19 classification in X-ray images using a new deep learning framework.

Journal of X-ray science and technology
BackgroundThe global concern regarding the diagnosis of lung-related diseases has intensified due to the rapid transmission of coronavirus disease 2019 (COVID-19). Artificial Intelligence (AI) based methods are emerging technologies that help to iden...

Mitigating bias in AI mortality predictions for minority populations: a transfer learning approach.

BMC medical informatics and decision making
BACKGROUND: The COVID-19 pandemic has highlighted the crucial role of artificial intelligence (AI) in predicting mortality and guiding healthcare decisions. However, AI models may perpetuate or exacerbate existing health disparities due to demographi...

Predicting work ability impairment in post COVID-19 patients: a machine learning model based on clinical parameters.

Infection
The Post COVID-19 condition (PCC) is a complex disease affecting health and everyday functioning. This is well reflected by a patient's inability to work (ITW). In this study, we aimed to investigate factors associated with ITW (1) and to design a ma...

Role of Artificial Intelligence in Identifying Vital Biomarkers with Greater Precision in Emergency Departments During Emerging Pandemics.

International journal of molecular sciences
The COVID-19 pandemic has accelerated advances in molecular biology and virology, enabling the identification of key biomarkers to differentiate between severe and mild cases. Furthermore, the use of artificial intelligence (AI) and machine learning ...

A machine learning-based analysis for the effectiveness of online teaching and learning in Pakistan during COVID-19 lockdown.

Work (Reading, Mass.)
BackgroundThe COVID-19 pandemic has significantly disrupted daily life and education, prompting institutions to adopt online teaching.ObjectiveThis study delves into the effectiveness of these methods during the lockdown in Pakistan, employing machin...

Interpretation of COVID-19 Epidemiological Trends in Mexico Through Wastewater Surveillance Using Simple Machine Learning Algorithms for Rapid Decision-Making.

Viruses
Detection and quantification of disease-related biomarkers in wastewater samples, denominated Wastewater-based Surveillance (WBS), has proven a valuable strategy for studying the prevalence of infectious diseases within populations in a time- and res...

Leveraging dynamics informed neural networks for predictive modeling of COVID-19 spread: a hybrid SEIRV-DNNs approach.

Scientific reports
A dynamics informed neural networks (DINNs) incorporating the susceptible-exposed-infectious-recovered-vaccinated (SEIRV) model was developed to enhance the understanding of the temporal evolution dynamics of infectious diseases. This work integrates...

A cross-sectional study of parental perspectives on children about COVID-19 and classification using machine learning models.

Frontiers in public health
BACKGROUND AND OBJECTIVE: This study delves into the parenting cognition perspectives on COVID-19 in children, exploring symptoms, transmission modes, and protective measures. It aims to correlate these perspectives with sociodemographic factors and ...

Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial.

Journal of medical Internet research
BACKGROUND: With increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment meth...