The codes for our proposed deep learning-based computational model, which aims to capture the developing asymmetry over longitudinal screening mammogram examinations for breast cancer risk prediction, are stored in this repository. The model was published in the Pattern Recognition journal under the title "Deep learning of longitudinal mammogram examinations for breast cancer risk prediction".
The published paper can be accessed at this link: https://www.sciencedirect.com/science/article/abs/pii/S0031320322004009.
Please use this citation:
@article{dadsetan2022deep, title={Deep learning of longitudinal mammogram examinations for breast cancer risk prediction}, author={Dadsetan, Saba and Arefan, Dooman and Berg, Wendie A and Zuley, Margarita L and Sumkin, Jules H and Wu, Shandong}, journal={Pattern Recognition}, volume={132}, pages={108919}, year={2022}, publisher={Elsevier} }