AI Medical Compendium Journal:
Journal of exposure science & environmental epidemiology

Showing 1 to 10 of 11 articles

MyEcoReporter: a prototype for artificial intelligence-facilitated pollution reporting.

Journal of exposure science & environmental epidemiology
BACKGROUND: Many chemical releases are first noticed by community members, but reporting these concerns often involves considerable hurdles. Artificial Intelligence (AI)-enabled technologies, especially large language models (LLMs), can potentially r...

Unmasking the sky: high-resolution PM prediction in Texas using machine learning techniques.

Journal of exposure science & environmental epidemiology
BACKGROUND: Although PM (fine particulate matter with an aerodynamic diameter less than 2.5 µm) is an air pollutant of great concern in Texas, limited regulatory monitors pose a significant challenge for decision-making and environmental studies.

Evaluating long-term and high spatiotemporal resolution of wet-bulb globe temperature through land-use based machine learning model.

Journal of exposure science & environmental epidemiology
BACKGROUND: The increase in global temperature and urban warming has led to the exacerbation of heatwaves, which negatively affect human health and cause long-term loss of work productivity. Therefore, a global assessment in temperature variation is ...

Application of artificial intelligence in quantifying lung deposition dose of black carbon in people with exposure to ambient combustion particles.

Journal of exposure science & environmental epidemiology
BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophag...

Socioexposomics of COVID-19 across New Jersey: a comparison of geostatistical and machine learning approaches.

Journal of exposure science & environmental epidemiology
BACKGROUND: Disparities in adverse COVID-19 health outcomes have been associated with multiple social and environmental stressors. However, research is needed to evaluate the consistency and efficiency of methods for studying these associations at lo...

Measuring and modelling perceptions of the built environment for epidemiological research using crowd-sourcing and image-based deep learning models.

Journal of exposure science & environmental epidemiology
BACKGROUND: Perceptions of the built environment, such as nature quality, beauty, relaxation, and safety, may be key factors linking the built environment to human health. However, few studies have examined these types of perceptions due to the diffi...

Modeling the transplacental transfer of small molecules using machine learning: a case study on per- and polyfluorinated substances (PFAS).

Journal of exposure science & environmental epidemiology
BACKGROUND: Despite their large numbers and widespread use, very little is known about the extent to which per- and polyfluoroalkyl substances (PFAS) can cross the placenta and expose the developing fetus.

Prediction of daily mean and one-hour maximum PM concentrations and applications in Central Mexico using satellite-based machine-learning models.

Journal of exposure science & environmental epidemiology
BACKGROUND: Machine-learning algorithms are becoming popular techniques to predict ambient air PM concentrations at high spatial resolutions (1 × 1 km) using satellite-based aerosol optical depth (AOD). Most machine-learning models have aimed to pred...

A deep learning approach to identify smoke plumes in satellite imagery in near-real time for health risk communication.

Journal of exposure science & environmental epidemiology
BACKGROUND: Wildland fire (wildfire; bushfire) pollution contributes to poor air quality, a risk factor for premature death. The frequency and intensity of wildfires are expected to increase; improved tools for estimating exposure to fire smoke are v...

Exploring the utility of robots in exposure studies.

Journal of exposure science & environmental epidemiology
Obtaining valid, reliable quantitative exposure data can be a significant challenge for industrial hygienists, exposure scientists, and other health science professionals. In this proof-of-concept study, a robotic platform was programmed to perform a...