In this study, a minimum distance classification and forward feature selection technique are joined to determine the relationship between weather conditions and the increase of the risk of type A acute aortic dissection (AAD) events in Berlin. The results demonstrate that changes in the amount of cloudiness and air temperature are the most representative weather predictors among the studied parameters. A discrimination surface was developed for the prediction of AAD events 6 h ahead, and it is found that, under a specific amount of cloudiness and air temperature, the risk of AAD events in Berlin increases about 20 %.
Keywords: Air temperature; Berlin; Cloudiness; Supervised classification technique; Type A acute aortic dissection; Weather predictors.