Environmental predictors and machine learning models for climate-health risk prediction from extreme weather events: a global systematic review

Climate change is increasing the frequency, severity, and duration of extreme weather events, including heatwaves, floods, and heavy rainfall, posing substantial risks to population health worldwide. Traditional epidemiological approaches capture retrospective associations but are limited in modelin...

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Detalhes bibliográficos

Principais autores:	Fahad Ayaz, Adam Ashford, Muhammad Zeeshan Shakir, Naeem Ramzan, Michael Gebreslasie, Serestina Viriri, David Ndzi, Natalie Dickinson, Llinos Haf Spencer, Mary Lynch, Fiona Henriquez-Mui, Ozayr Mahomed, Saloshni Naidoo, Nisha Nadesan-Reddy
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2026-07-01
coleção:	Frontiers in Climate
Assuntos:	climate-sensitive health outcome prediction environmental exposure extreme weather events machine learning systematic review
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fclim.2026.1843933/full
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