This data package contains the information needed to replicate the research titled - 'Predicting overall survival of NSCLC patients with clinical, radiomics and deep learning features'.

This research is part of the AMICUS project. The anonymized clinical research data from Maastro is used for this research. This data is present in the research servers at Maastro. This research is a joint effort between Tilburg and Maastro. Hemalatha Kanakarajan(Tilburg University) and Jikai Zhou (Maastro) are the shared first authors of the paper. Due to privacy reasons, data cannot be moved out of Maastro. The data can be accessed after approval from Maastro. The Python scripts used for the model development are attached with this dataset.

This research developed a model to predict the overall survival of NSCLC patients using clinical, radiomics and deep learning features. This research can be replicated by following the methodology described in the paper.