ArticleEmergency medicine international2022
A Machine Learning-Based Study of the Effects of Air Pollution and Weather in Respiratory Disease Patients Visiting Emergency Departments.
Article in Emergency medicine international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Artificial intelligence risk prediction model for common respiratory pathogens in China based on heterogeneous multi-source clinical and geographic data: A modeling study.PLOS digital health · 2026Article
- Prediction of the respiratory disease incidence based on environmental factors using machine learning techniques in Penang, Malaysia.Scientific reports · 2026Article
- Respiratory incidents in response to air quality deterioration in the summer and early autumn season.PloS one · 2025Article
- Forecasting of influenza activity and associated hospital admission burden and estimating the impact of COVID-19 pandemic on 2019/20 winter season in Hong Kong.PLoS computational biology · 2024Article
- Ambient air pollution, temperature and hospital admissions due to respiratory diseases in a cold, industrial city.Journal of global health · 2022Article
- Influenza incidence and air pollution: Findings from a four-year surveillance study of prefecture-level cities in China.Frontiers in public health · 2022Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo date, investigating respiratory disease patients visiting the emergency departments related with fined dust is limited. This study aimed to analyze the effects of two variable-weather and air pollution on respiratory disease patients who visited emergency departments.
methodsThis study utilized the National Emergency Department Information System (NEDIS) database. The meteorological data were obtained from the National Climate Data Service. Each weather factor reflected the accumulated data of 4 days: a patient's visit day and 3 days before the visit day. We utilized the RandomForestRegressor of scikit-learn for data analysis.
resultThe study included 525,579 participants. This study found that multiple variables of weather and air pollution influenced the respiratory diseases of patients who visited emergency departments. Most of the respiratory disease patients had acute upper respiratory infections [J00-J06], influenza [J09-J11], and pneumonia [J12-J18], on which PM
conclusionMost of the respiratory patients visiting EDs were diagnosed with acute upper respiratory infections, influenza, and pneumonia. Following temperature, steam pressure and PM
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Registered trials
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