LUADnet: a deep learning model for prediction of clinical outcomes in lung adenocarcinoma based on gene expression signatures

Lung adenocarcinoma (LUAD) is the most prevalent subtype of non-small cell lung cancer (NSCLC), and immunochemotherapy is widely utilized in its treatment. However, there are several drawbacks, including immune escape, immune-related adverse events (irAEs), a significant economic burden, and unfavorable outcomes. Therefore, it is crucial to identify patients who are likely to respond to non-immunotherapy.