Non-small cell lung cancer (NSCLC) is one of the cancers with the highest incidence and mortality rates worldwide. Accurate prognostic models can guide clinical treatment plans. With the continuous upgrading of computer technology, deep learning, as a breakthrough technology in artificial intelligence, has shown good performance and great potential in the application of NSCLC prognostic models. Research on the application of deep learning in the prediction of NSCLC survival and recurrence, therapeutic efficacy, distant metastasis, and complications has made certain progress and is showing a trend of multi-omics and multi-modal integration. However, there are still some deficiencies. In the future, in-depth exploration should be carried out, model validation should be strengthened, and clinical practical problems should be solved.
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