Predicting acute and long-term mortality in a cohort of pulmonary embolism patients using machine learning

Venous thromboembolism (VTE), including both pulmonary embolism (PE) and deep vein thrombosis (DVT), is a severe condition that causes significant mortality and morbidity in the acute phase, with a mortality rate equivalent to that of ischaemic stroke [1]. A significant proportion of mortality is due to heart failure post-PE [2], with a large meta-analysis reporting a mortality of 10.7% [3].