BACKGROUND: The COVID-19 pandemic exacerbated issues of poverty and food insecurity in New York City, and many residents experienced difficulty accessing available resources to help them get food on the table. Social media presents an opportunity to ...
In the quest to ensure adequate preparedness for health emergencies caused by infectious disease pandemics, there is a need for tools that can address the myriad relevant questions related to the spread and trajectory of pandemics. A hybrid intellige...
As we move beyond the COVID-19 pandemic, the risk of future infodemics remains significant, driven by emerging health crises and the increasing influence of artificial intelligence in the information ecosystem. During periods of apparent stability, p...
AIMS: Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and behaviours (STBs) among healthcare workers (HCWs). The current study aimed to (1) develop a machine learning-based prediction model for future STBs us...
We propose a new theory of information-based voluntary social distancing in which people's responses to disease prevalence depend on the credibility of reported cases and fatalities and vary locally. We embed this theory into a new pandemic predictio...
The emergence of the SARS-CoV-2 virus and the resulting COVID-19 pandemic brought forth an urgent need for an in-depth molecular understanding, organization, and data integration to expedite therapeutic and preventive strategies. An essential approac...
The digital transformation of healthcare is revolutionizing the management of medical institutions, improving operational efficiency, patient outcomes, and data security. With the increasing complexity of healthcare systems, the integration of cuttin...
Stress and health : journal of the International Society for the Investigation of Stress
40261245
Online self-guided interventions appear efficacious for alleviating some mental health concerns. However, among persons who are offered online interventions, only a fraction access them (i.e., achieve uptake). Machine learning methods may be useful t...
BACKGROUND: The COVID-19 pandemic intensified the challenges associated with mental health and substance use (SU), with societal and economic upheavals leading to heightened stress and increased reliance on drugs as a coping mechanism. Centers for Di...
This study presents a neural network-based framework for COVID-19 transmission prediction and healthcare resource optimization. The model achieves high prediction accuracy by integrating epidemiological, mobility, vaccination, and environmental data ...