Machine learning and spatio-temporal analysis of meteorological factors on waterborne diseases in Bangladesh.
- Published in:
- PLoS Neglected Tropical Diseases, 2025, v. 19, n. 1, p. 1, doi. 10.1371/journal.pntd.0012800
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- Publication type:
- Article
Works matching AU Chowdhury, Arman Hossain
Results: 6
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2
Comparison of Deep Learning and Gradient Boosting: ANN Versus XGBoost for Climate‐Based Dengue Prediction in Bangladesh.
- Published in:
- Health Science Reports, 2025, v. 8, n. 4, p. 1, doi. 10.1002/hsr2.70714
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- Publication type:
- Article
3
Spatio‐temporal pattern and associate meteorological factors of airborne diseases in Bangladesh using geospatial mapping and spatial regression model.
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- Health Science Reports, 2024, v. 7, n. 6, p. 1, doi. 10.1002/hsr2.2176
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- Publication type:
- Article
4
Predicting anxiety, depression, and insomnia among Bangladeshi university students using tree‐based machine learning models.
- Published in:
- Health Science Reports, 2024, v. 7, n. 4, p. 1, doi. 10.1002/hsr2.2037
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- Publication type:
- Article
5
A tree based eXtreme Gradient Boosting (XGBoost) machine learning model to forecast the annual rice production in Bangladesh.
- Published in:
- PLoS ONE, 2023, v. 18, n. 3, p. 1, doi. 10.1371/journal.pone.0283452
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- Publication type:
- Article
6
A data-driven eXtreme gradient boosting machine learning model to predict COVID-19 transmission with meteorological drivers.
- Published in:
- PLoS ONE, 2022, v. 17, n. 9, p. 1, doi. 10.1371/journal.pone.0273319
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- Publication type:
- Article