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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:

Social implementation and intervention with estimated morbidity of heat-related illnesses from weather data: A case study from Nagoya City, Japan
Taku Nishimura, Essam A. Rashed, Sachiko Kodera, et al.
Sustainable Cities and Society (2021) Vol. 74, pp. 103203-103203
Closed Access | Times Cited: 18

Showing 18 citing articles:

Is dense or sprawl growth more prone to heat-related health risks? Spatial regression-based study in Delhi, India
Suvamoy Pramanik, Milap Punia, Hanchen Yu, et al.
Sustainable Cities and Society (2022) Vol. 81, pp. 103808-103808
Closed Access | Times Cited: 29
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
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
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
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
Understanding EMS response times: a machine learning-based analysis
Peter Hill, Jakob Lederman, Daniel Jönsson, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Projection of future heat-related morbidity in three metropolitan prefectures of Japan based on large ensemble simulations of climate change under 2 °C global warming scenarios
Haruto Ueta, Sachiko Kodera, Shiori Sugimoto, et al.
Environmental Research (2024) Vol. 247, pp. 118202-118202
Open Access | Times Cited: 3
Estimation of the number of heat illness patients in eight metropolitan prefectures of Japan: Correlation with ambient temperature and computed thermophysiological responses
Akito Takada, Sachiko Kodera, Koji Suzuki, et al.
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 6
Body Core Temperature Estimation Using New Compartment Model With Vital Data From Wearable Devices
Akimasa Hirata, Taiki Miyazawa, Ryota Uematsu, et al.
IEEE Access (2021) Vol. 9, pp. 124452-124462
Open Access | Times Cited: 9
Respiratory Diseases Prediction from a Novel Chaotic System
Mohammed Mansour, Turker Berk Donmez, Mustafa Kutlu, et al.
Chaos Theory and Applications (2023) Vol. 5, Iss. 1, pp. 20-26
Open Access | Times Cited: 3
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
Tools for optimizing healthcare resource allocation in response to climate impacts and heat action planning
Jakob Thiel, Anne Seim, Sophia Grummt, et al.
Journal of Public Health (2024)
Open Access
Optimizing EMS Response Times with Machine Learning: A Multivariate Analysis for Enhanced Resource Allocation
Peter Hill, Jakob Lederman, Daniel Jönsson, et al.
Research Square (Research Square) (2024)
Open Access
Evaluation of effectiveness and resources consumption of water mist spray systems in Mediterranean areas by predictions based on LSTM Recurrent Neural Networks
Marco D’Orazio, Costanzo Di Perna, Elisa Di Giuseppe, et al.
Sustainable Cities and Society (2023) Vol. 99, pp. 104894-104894
Open Access | Times Cited: 1
Predicting the risk of heatstroke: Development of a highly accurate model
Mio Nemoto, Satoshi Hirabayashi, Seisho Sato, et al.
Research Square (Research Square) (2023)
Open Access
Predicting the risk of heatstroke: Development of a highly accurate model
Mio Nemoto, Satoshi Hirabayashi, Seisho Sato, et al.
Research Square (Research Square) (2023)
Open Access
Comparative evaluation of accuracy of the multiple methods of heatstroke risk model including time-stratified case-crossover analysis
Mio Nemoto, Satoshi Hirabayashi, Seisho Sato, et al.
Research Square (Research Square) (2022)
Open Access
Comparative evaluation of accuracy of the multiple methods of heatstroke risk model including time-stratified case-crossover analysis
Mio Nemoto, Satoshi Hirabayashi, Seisho Sato, et al.
Research Square (Research Square) (2022)
Open Access
Predicting the risk of heatstroke: Development of a highly accurate model
Mio Nemoto, Satoshi Hirabayashi, Seisho Sato, et al.
Research Square (Research Square) (2022)
Open Access
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