Cancer Recurrence

The aim of this project is to perform multimodal fusion of CT images (radiology) and RNA-sequencing based gene expression data (genomics) for post-surgical recurrence prediction in lung cancer

With the combined data from CT scan images and gene expression we performed machine learning and deep learning techniques to extract meaningful radiomic descriptors and best genes from these data. The c-index values has been calculated to quantify the correlation and impact of these descriptors in the final optimal model