Lung Cancer Recurrence Risk Prediction through Integrated Deep Learning Evaluation.

In the multivariate proportional hazards regression model that included IDLE, TNM staging, tumor grade, and the potential confounding variables (age at surgery, chemotherapy, and radiotherapy received either before or after the surgery) ( Table 2 ), both TNM staging and tumor grade lost statistical association with cancer progression ( p > 0.63) when IDLE was included in the model, while the association of IDLE with progression was highly significant (HR = 5.671, 95% CI = 3.1650–10.1605, p < 0.0001).

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