Deep learning models to predict lung cancer malignancy
The National Lung Screening Trial (NLST) contains LDCT images for patients with lung cancers and with benign nodules. We plan to utilize deep learning, radiomics, and clinical data to create an accurate prediction model to estimate lung nodule malignancy from LDCT images.
We aim to divide the data into training, validation, and testing set. Each set will contain malignant and benign nodules. We plan to train and validate a deep learning model that combines image features, radiomic features, and clinical features to accurately characterize nodule malignancy. We are aiming for sensitivity and specificity over 90%.
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