Development and validation of an explainable machine learning model for mortality prediction in ICU patients with lung cancer (opens in new tab)

Background and ObjectiveLung cancer is the leading cause of cancer-related death worldwide, with a particularly high mortality risk among patients admitted to the intensive care unit (ICU). Accurate and timely prediction of in-hospital mortality in this population is critical for clinical decision-making and resource allocation. However, existing severity scoring systems have demonstrated limited discriminative performance in this specific context. This study aimed to develop and validate an ...