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Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images.

, , , , , and . CoRR, (2019)

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A Modified AUC for Training Convolutional Neural Networks: Taking Confidence into Account., , and . CoRR, (2020)Improving Prognostic Performance in Resectable Pancreatic Ductal Adenocarcinoma using Radiomics and Deep Learning Features Fusion in CT Images., , , , , and . CoRR, (2019)Prognostic Value of Transfer Learning Based Features in Resectable Pancreatic Ductal Adenocarcinoma., , , , , and . Frontiers Artif. Intell., (2020)A Modified AUC for Training Convolutional Neural Networks: Taking Confidence Into Account., , and . Frontiers Artif. Intell., (2021)Supervised prostate cancer segmentation with multispectral MRI incorporating location information., , and . ISBI, page 1496-1499. IEEE, (2011)A task-based approach to parametric imaging with dynamic contrast enhanced MRI., , and . ISBI, page 746-749. IEEE, (2011)CNN-based survival model for pancreatic ductal adenocarcinoma in medical imaging., , , , , and . BMC Medical Imaging, 20 (1): 11 (2020)CNN-based Survival Model for Pancreatic Ductal Adenocarcinoma in Medical Imaging., , , , , and . CoRR, (2019)Prostate Cancer Segmentation With Simultaneous Estimation of Markov Random Field Parameters and Class., , , , , and . IEEE Trans. Medical Imaging, 28 (6): 906-915 (2009)Automated prostate cancer localization with MRI without the need of manually extracted peripheral zone., , and . ISBI, page 2099-2102. IEEE, (2011)