ArticleNature communications2021
Heatstroke predictions by machine learning, weather information, and an all-population registry for 12-hour heatstroke alerts.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Prevalence of disability-free survival at 5 years after surgery: a prospective observational study.Journal of anesthesia · 2026Article
- Investigating the Association Between Heatstroke Mortality and Climatic Factors in Bangladesh: An Ecological Time Series Study.Health science reports · 2026Article
- Decoding the Primacy of Transportation Emissions of Formaldehyde Pollution in an Urban Atmosphere.Toxics · 2025Article
- Machine learning-based forecasting of daily acute ischemic stroke admissions using weather data.NPJ digital medicine · 2025Article
- Article
- The pathogenesis and therapeutic strategies of heat stroke-induced endothelial injury.Frontiers in cell and developmental biology · 2025Review
- Article
- Developing a molecular diagnostic model for heatstroke-induced coagulopathy: a proteomics and metabolomics approach.Frontiers in molecular biosciences · 2025Article
- The use of machine and deep learning to model the relationship between discomfort temperature and labor productivity loss among petrochemical workers.BMC public health · 2024Article
- Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HEBMJ open · 2024Article
- Identifying potential (re)hemorrhage among sporadic cerebral cavernous malformations using machine learning.Scientific reports · 2024Article
- The spatiotemporal trend of human brucellosis in China and driving factors using interpretability analysis.Scientific reports · 2024Article
- Development and validation of a prognostic model of survival for classic heatstroke patients: a multicenter study.Scientific reports · 2023Article
- Machine learning analysis and risk prediction of weather-sensitive mortality related to cardiovascular disease during summer in Tokyo, Japan.Scientific reports · 2023Article
- Socio-Environmental Determinants of Mental and Behavioral Disorders in Youth: A Machine Learning Approach.GeoHealth · 2023Article
- Estimation of the number of heat illness patients in eight metropolitan prefectures of Japan: Correlation with ambient temperature and computed thermophysiological responses.Frontiers in public health · 2023Article
- Possible adaptation measures for climate change in preventing heatstroke among older adults in Japan.Frontiers in public health · 2023Article
- Heatstroke-induced coagulopathy: Biomarkers, mechanistic insights, and patient management.EClinicalMedicine · 2022Review
- Baseline scenarios of heat-related ambulance transportations under climate change in Tokyo, Japan.PeerJ · 2022Article
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Authors and funding
17 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aims to develop and validate prediction models for the number of all heatstroke cases, and heatstrokes of hospital admission and death cases per city per 12 h, using multiple weather information and a population-based database for heatstroke patients in 16 Japanese cities (corresponding to around a 10,000,000 population size). In the testing dataset, mean absolute percentage error of generalized linear models with wet bulb globe temperature as the only predictor and the optimal models, respectively, are 43.0% and 14.8% for spikes in the number of all heatstroke cases, and 37.7% and 10.6% for spikes in the number of heatstrokes of hospital admission and death cases. The optimal models predict the spikes in the number of heatstrokes well by machine learning methods including non-linear multivariable predictors and/or under-sampling and bagging. Here, we develop prediction models whose predictive performances are high enough to be implemented in public health settings.
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