Deep learning for lung cancer prognostication: A retrospective multi-cohort radiomics study

por Hosny, Ahmed, Parmar, Chintan, Coroller, Thibaud P., Grossmann, Patrick, Zeleznik, Roman, Kumar, Avnish, Bussink, Johan, Gillies, Robert J., Mak, Raymond H., Aerts, Hugo J. W. L.
Publicado 2018

The impact of quantitative CT-based tumor volumetric features on the outcomes of patients with limited stage small cell lung cancer

por Kamran, Sophia C., Coroller, Thibaud, Milani, Nastaran, Agrawal, Vishesh, Baldini, Elizabeth H., Chen, Aileen B., Johnson, Bruce E., Kozono, David, Franco, Idalid, Chopra, Nitish, Zeleznik, Roman, Aerts, Hugo J. W. L., Mak, Raymond
Publicado 2020

Deep-learning system to improve the quality and efficiency of volumetric heart segmentation for breast cancer

por Zeleznik, Roman, Weiss, Jakob, Taron, Jana, Guthier, Christian, Bitterman, Danielle S., Hancox, Cindy, Kann, Benjamin H., Kim, Daniel W., Punglia, Rinaa S., Bredfeldt, Jeremy, Foldyna, Borek, Eslami, Parastou, Lu, Michael T., Hoffmann, Udo, Mak, Raymond, Aerts, Hugo J. W. L.
Publicado 2021

Benchmarking omics-based prediction of asthma development in children

por Wang, Xu-Wen, Wang, Tong, Schaub, Darius P., Chen, Can, Sun, Zheng, Ke, Shanlin, Hecker, Julian, Maaser-Hecker, Anna, Zeleznik, Oana A., Zeleznik, Roman, Litonjua, Augusto A., DeMeo, Dawn L., Lasky-Su, Jessica, Silverman, Edwin K., Liu, Yang-Yu, Weiss, Scott T.
Publicado 2023

Deep convolutional neural networks to predict cardiovascular risk from computed tomography

por Zeleznik, Roman, Foldyna, Borek, Eslami, Parastou, Weiss, Jakob, Alexander, Ivanov, Taron, Jana, Parmar, Chintan, Alvi, Raza M., Banerji, Dahlia, Uno, Mio, Kikuchi, Yasuka, Karady, Julia, Zhang, Lili, Scholtz, Jan-Erik, Mayrhofer, Thomas, Lyass, Asya, Mahoney, Taylor F., Massaro, Joseph M., Vasan, Ramachandran S., Douglas, Pamela S., Hoffmann, Udo, Lu, Michael T., Aerts, Hugo J. W. L.
Publicado 2021