Predictive Analytics

WE-STORM > Stroke > Ischemic stroke 
The project is now available as preprint on medRxiv:

Machine learning-based forecasting of daily acute ischemic stroke admissions using weather data
Previous work
Annual Meeting of the German Neuroradiology Society 2023 (DGNR) 10/05 - 10/06/2023

Power Pitch & Poster presentations, ID 259 & 325, 2023-10-05 & 06 

Predicting ischemic stroke admissions based on weather patterns for improved clinical resource allocation using machine learning

Background: Weather factors like temperature, pressure, and humidity contribute to stroke risk, which will be potentiated by the impending global climate crisis [1]. Our study aimed to predict the number of ischemic stroke cases at clinically relevant time resolutions in order to improve healthcare resource allocation. [ ...]

WE-STORM > Bleeding > Intracranial- (ICH) & Subarachnoid hemorrhage (SAH)
10th European Stroke Organisation Conference (ESOC) 05/15 - 05/17/2024

Poster presentation, P0165 Epidemiology & Risk Factors, 2024-05-16 

Rainstorms with a splash of blood: machine learning-based predictive analytics for hemorrhagic stroke admission based on  weather systems

Background: The climate crisis impacts cardiovascular health and stroke, contributing significantly to the global disease burden. Weather-based disease surveillance for healthcare providers is lacking.

Aim: Hence, we aimed to forecast the number of daily hemorrhagic stroke admissions based on meteorological parameters by applying machine learning models. [...]

Poster as PDF is available here: