Articles | Volume 22, issue 9
Research article
16 Sep 2022
Research article |  | 16 Sep 2022

Machine learning models to predict myocardial infarctions from past climatic and environmental conditions

Lennart Marien, Mahyar Valizadeh, Wolfgang zu Castell, Christine Nam, Diana Rechid, Alexandra Schneider, Christine Meisinger, Jakob Linseisen, Kathrin Wolf, and Laurens M. Bouwer


Total article views: 1,680 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,334 310 36 1,680 19 19
  • HTML: 1,334
  • PDF: 310
  • XML: 36
  • Total: 1,680
  • BibTeX: 19
  • EndNote: 19
Views and downloads (calculated since 07 Jan 2022)
Cumulative views and downloads (calculated since 07 Jan 2022)

Viewed (geographical distribution)

Total article views: 1,680 (including HTML, PDF, and XML) Thereof 1,593 with geography defined and 87 with unknown origin.
Country # Views %
  • 1

Discussed (final revised paper)

Latest update: 27 Mar 2023
Short summary
Myocardial infarctions (MIs; heart attacks) are influenced by temperature extremes, air pollution, lack of green spaces and ageing population. Here, we apply machine learning (ML) models in order to estimate the influence of various environmental and demographic risk factors. The resulting ML models can accurately reproduce observed annual variability in MI and inter-annual trends. The models allow quantification of the importance of individual factors and can be used to project future risk.
Final-revised paper