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Convolutional neural network-based decision support system for bladder cancer staging in CT urography: decision threshold estimation and validation.

D. Chapman-Sung, L. Hadjiiski, D. Gandikota, H. Chan, R. Samala, E. Caoili, R. Cohan, A. Weizer, A. Alva, and C. Zhou. Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)

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Reinforcement Learning for Wildfire Mitigation in Simulated Disaster Environments.A. Tapley, M. Dotter, M. Doyle, A. Fennelly, D. Gandikota, S. Smith, M. Threet, and T. Welsh. CoRR, (2023)Convolutional neural network-based decision support system for bladder cancer staging in CT urography: decision threshold estimation and validation.D. Chapman-Sung, L. Hadjiiski, D. Gandikota, H. Chan, R. Samala, E. Caoili, R. Cohan, A. Weizer, A. Alva, and C. Zhou. Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)Bladder cancer staging in CT urography: estimation and validation of decision thresholds for a radiomics-based decision support system.D. Gandikota, L. Hadjiiski, H. Chan, K. Cha, R. Samala, E. Caoili, R. Cohan, A. Weizer, A. Alva, C. Paramagul and 2 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 109500W. SPIE, (2019)AI Augmentation to Remote Sensing Imagery in Forestry Conservation & Restoration for Increased Responsive Capabilities.D. Gandikota, T. Gladkova, K. Tran, S. Bapat, J. Richkus, and J. Arnold. AIPR, page 1-16. IEEE, (2022)

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Convolutional neural network-based decision support system for bladder cancer staging in CT urography: decision threshold estimation and validation.

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