CNN-based Methods for Survival Prediction using CT images for Lung Cancer Patients

Lung Cancer (LC) is still among the top main causes of death worldwide, and it is the leading death number among other cancers. Several AI-based methods have been developed for the early detection of LC, trying to use Computed Tomography (CT) images to identify the initial signs of the disease. The survival prediction could help the clinicians to adequate the treatment plan and all the proceedings, by the identification of the most severe cases that need more attention. In this study, several deep learning models were compared to predict the survival of LC patients using CT images. The best performing model, a CNN with 3 layers, achieved an AUC value of 0.80, a Precision value of 0.56 and a Recall of 0.64. The obtained results showed that CT images carry information that can be used to assess the survival of LC.