AIMC Topic: Meteorological Concepts
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Optimizing BenMAP health impact assessment with meteorological factor driven machine learning models.
The Science of the total environment
Aug 3, 2024
This study aims to address accuracy challenges in assessing air pollution health impacts using Environmental Benefits Mapping and Analysis Program (BenMap), caused by limited meteorological factor data and missing pollutant data. By employing data in...
The Lag -Effects of Air Pollutants and Meteorological Factors on COVID-19 Infection Transmission and Severity: Using Machine Learning Techniques.
Journal of research in health sciences
Jul 31, 2024
BACKGROUND: Exposure to air pollution is a major health problem worldwide. This study aimed to investigate the effect of the level of air pollutants and meteorological parameters with their related lag time on the transmission and severity of coronav...
Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors.
Environmental monitoring and assessment
Jul 24, 2024
This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory dise...
Machine learning-based analysis and prediction of meteorological factors and urban heatstroke diseases.
Frontiers in public health
Jul 22, 2024
INTRODUCTION: Heatstroke is a serious clinical condition caused by exposure to high temperature and high humidity environment, which leads to a rapid increase of the core temperature of the body to more than 40°C, accompanied by skin burning, conscio...
Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model.
BMC infectious diseases
Feb 26, 2024
BACKGROUND: Infectious diarrhea remains a major public health problem worldwide. This study used stacking ensemble to developed a predictive model for the incidence of infectious diarrhea, aiming to achieve better prediction performance.
Meteorological factors cannot be ignored in machine learning-based methods for predicting dengue, a systematic review.
International journal of biometeorology
Dec 27, 2023
In recent years, there has been a rapid increase in the application of machine learning methods about predicting the incidence of dengue fever. However, the predictive factors and models employed in different studies vary greatly. Hence, we conducted...
Spatio-temporal fusion of meteorological factors for multi-site PM2.5 prediction: A deep learning and time-variant graph approach.
Environmental research
Oct 4, 2023
In the field of environmental science, traditional methods for predicting PM2.5 concentrations primarily focus on singular temporal or spatial dimensions. This approach presents certain limitations when it comes to deeply mining the joint influence o...
ELoran Propagation Delay Prediction Model Based on a BP Neural Network for a Complex Meteorological Environment.
Sensors (Basel, Switzerland)
May 29, 2023
The core of eLoran ground-based timing navigation systems is the accurate measurement of groundwave propagation delay. However, meteorological changes will disturb the conductive characteristic factors along the groundwave propagation path, especiall...
Deep learning models for hepatitis E incidence prediction leveraging meteorological factors.
PloS one
Mar 13, 2023
BACKGROUND: Infectious diseases are a major threat to public health, causing serious medical consumption and casualties. Accurate prediction of infectious diseases incidence is of great significance for public health organizations to prevent the spre...
Interpretable machine learning approach to analyze the effects of landscape and meteorological factors on mosquito occurrences in Seoul, South Korea.
Environmental science and pollution research international
Jul 28, 2022
Mosquitoes are the underlying cause of various public health and economic problems. In this study, patterns of mosquito occurrence were analyzed based on landscape and meteorological factors in the metropolitan city of Seoul. We evaluated the influen...
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