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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine and deep learning for modelling heat-health relationships
Jérémie Boudreault, Céline Campagna, Fateh Chebana
The Science of The Total Environment (2023) Vol. 892, pp. 164660-164660
Open Access | Times Cited: 18

Showing 18 citing articles:

DESignSolvents: an open platform for the search and prediction of the physicochemical properties of deep eutectic solvents
Valeria Odegova, Anastasia K. Lavrinenko, Timur Rakhmanov, et al.
Green Chemistry (2024) Vol. 26, Iss. 7, pp. 3958-3967
Closed Access | Times Cited: 13
Deep optimization of water quality index and positive matrix factorization models for water quality evaluation and pollution source apportionment using a random forest model
Han Zhang, Xingnian Ren, Sikai Chen, et al.
Environmental Pollution (2024) Vol. 347, pp. 123771-123771
Closed Access | Times Cited: 13
Revisiting the importance of temperature, weather and air pollution variables in heat-mortality relationships with machine learning
Jérémie Boudreault, Céline Campagna, Fateh Chebana
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 9, pp. 14059-14070
Closed Access | Times Cited: 5
Estimating the heat-related mortality and morbidity burden in the province of Quebec, Canada
Jérémie Boudreault, Éric Lavigne, Céline Campagna, et al.
Environmental Research (2024) Vol. 257, pp. 119347-119347
Open Access | Times Cited: 4
Multi-region models built with machine and deep learning for predicting several heat-related health outcomes
Jérémie Boudreault, Annabel Ruf, Céline Campagna, et al.
Sustainable Cities and Society (2024) Vol. 115, pp. 105785-105785
Open Access | Times Cited: 4
Integrating AI and climate change scenarios for multi-risk assessment in the coastal municipalities of the Veneto region
Maria Katherina Dal Barco, Margherita Maraschini, Ngoc Diep Nguyen, et al.
The Science of The Total Environment (2025) Vol. 965, pp. 178586-178586
Closed Access
Relative Fat Mass and Physical Indices as Predictors of Gallstone Formation: Insights From Machine Learning and Logistic Regression
Lei Deng, Shuting Wang, Daiwei Wan, et al.
International Journal of General Medicine (2025) Vol. Volume 18, pp. 509-527
Open Access
Revealing Key Factors of Heat-related Illnesses using Geospatial Explainable AI Model: A Case Study in Texas, USA
Ehsan Foroutan, Tao Hu, Ziqi Li
Sustainable Cities and Society (2025), pp. 106243-106243
Closed Access
Vulnerability assessment of heat waves within a risk framework using artificial intelligence
Jean-Nicolas Côté, Mickaël Germain, Elisabeth Levac, et al.
The Science of The Total Environment (2023) Vol. 912, pp. 169355-169355
Open Access | Times Cited: 5
A machine learning model predicts stroke associated with blood cadmium level
Wenwei Zuo, Xuelian Yang
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Random forest analysis of the relative importance of meteorological indicators for heatstroke cases in Japan based on the degree of severity and place of occurrence
Kazutaka Oka, Jinyu He, Yasushi Honda, et al.
Environmental Research (2024), pp. 120066-120066
Open Access | Times Cited: 1
Projected risk and vulnerability to heat waves for Montreal, Quebec, using Gaussian processes
Jean-Nicolas Côté, Elisabeth Levac, Mickaël Germain, et al.
Sustainable Cities and Society (2024), pp. 105907-105907
Open Access | Times Cited: 1
Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HE2AT Center study protocol
Christopher Jack, Craig Parker, Yao Etienne Kouakou, et al.
BMJ Open (2024) Vol. 14, Iss. 6, pp. e077529-e077529
Open Access
The Mechanism of Street Spatial Form on Thermal Comfort from Urban Morphology and Human-Centered Perspectives: A Study Based on Multi-Source Data
Fei Guo, Mingxuan Luo, Chenxi Zhang, et al.
Buildings (2024) Vol. 14, Iss. 10, pp. 3253-3253
Open Access
The use of machine and deep learning to model the relationship between discomfort temperature and labor productivity loss among petrochemical workers
Yilin Zhang, Yifeng Chen, Qingling Su, et al.
BMC Public Health (2024) Vol. 24, Iss. 1
Open Access
Forecasting Human Core and Skin Temperatures: A Long-Term Series Approach
Xinge Han, Jiansong Wu, Zhuqiang Hu, et al.
Big Data and Cognitive Computing (2024) Vol. 8, Iss. 12, pp. 197-197
Open Access
Application of Machine Learning Techniques for Predicting Students’ Acoustic Evaluation in a University Library
Dadi Zhang, Kwok Wai Mui, Massimiliano Masullo, et al.
Acoustics (2024) Vol. 6, Iss. 3, pp. 681-697
Open Access
Interdisciplinary methods for researching climate-mental health links through the Methane Early Warning Network (ME-NET): improving ‘visibility’ and integrating complex multi-datasets
Harriet Elizabeth Moore, John Atanbori, Ebenezer Forkuo Amankwaa, et al.
Research Directions Depression (2024) Vol. 1
Closed Access
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