Forecasting health outcomes of Air Pollution: A Statistical review of modelling techniques and applications

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Autores principales: Sonone, Pranjali Subhash, Khamborkar, Abhay Kamlakar
Formato: Recurso digital
Lenguaje:inglés
Publicado: Zenodo 2025
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author Sonone, Pranjali Subhash
Khamborkar, Abhay Kamlakar
author_facet Sonone, Pranjali Subhash
Khamborkar, Abhay Kamlakar
contents <p>This review summarises all recent papers related to the prediction of diseases caused by air pollution. Most of the papers identified through the literature review focused either on health risk prediction alone or air pollutant prediction in various regions. However, very few research articles are based on predictive models that provide health risk predictions and also assess the effects on health. Therefore, the primary objective of this review is to identify models that incorporate both air pollution data and health data to predict diseases. This review encompasses the shift from traditional models to machine learning models in forecasting. This study will be beneficial for future research aimed at identifying diseases caused solely by specific air pollutants.</p>
format Recurso digital
id zenodo_https___doi_org_10_5281_zenodo_17529228
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Forecasting health outcomes of Air Pollution: A Statistical review of modelling techniques and applications
Sonone, Pranjali Subhash
Khamborkar, Abhay Kamlakar
Review of Air Pollution Studies
Machine Learning
Air Pollution
Health Risk
Prediction of Disease
<p>This review summarises all recent papers related to the prediction of diseases caused by air pollution. Most of the papers identified through the literature review focused either on health risk prediction alone or air pollutant prediction in various regions. However, very few research articles are based on predictive models that provide health risk predictions and also assess the effects on health. Therefore, the primary objective of this review is to identify models that incorporate both air pollution data and health data to predict diseases. This review encompasses the shift from traditional models to machine learning models in forecasting. This study will be beneficial for future research aimed at identifying diseases caused solely by specific air pollutants.</p>
title Forecasting health outcomes of Air Pollution: A Statistical review of modelling techniques and applications
topic Review of Air Pollution Studies
Machine Learning
Air Pollution
Health Risk
Prediction of Disease
url https://doi.org/10.5281/zenodo.17529228