CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma von Coroller, Thibaud P, Grossmann, Patrick, Hou, Ying, Rios Velazquez, Emmanuel, Leijenaar, Ralph T.H, Hermann, Gretchen, Lambin, Philippe, Haibe-Kains, Benjamin, Mak, Raymond H, Aerts, Hugo J.W.L

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Radiomics: Extracting more information from medical images using advanced feature analysis von Lambin, Philippe, Rios-Velazquez, Emmanuel, Leijenaar, Ralph, Carvalho, Sara, van Stiphout, Ruud G.P.M, Granton, Patrick, Zegers, Catharina M.L, Gillies, Robert, Boellard, Ronald, Dekker, André, Aerts, Hugo J.W.L

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The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis von Leijenaar, Ralph T.H., Nalbantov, Georgi, Carvalho, Sara, van Elmpt, Wouter J.C., Troost, Esther G.C., Boellaard, Ronald, Aerts, Hugo J.W.L, Gillies, Robert J., Lambin, Philippe

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Deep learning to estimate lung disease mortality from chest radiographs von Weiss, Jakob, Raghu, Vineet K., Bontempi, Dennis, Christiani, David C., Mak, Raymond H., Lu, Michael T., Aerts, Hugo J.W.L.

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Automated temporalis muscle quantification and growth charts for children through adulthood von Zapaishchykova, Anna, Liu, Kevin X., Saraf, Anurag, Ye, Zezhong, Catalano, Paul J., Benitez, Viviana, Ravipati, Yashwanth, Jain, Arnav, Huang, Julia, Hayat, Hasaan, Likitlersuang, Jirapat, Vajapeyam, Sridhar, Chopra, Rishi B., Familiar, Ariana M., Nabavidazeh, Ali, Mak, Raymond H., Resnick, Adam C., Mueller, Sabine, Cooney, Tabitha M., Haas-Kogan, Daphne A., Poussaint, Tina Y., Aerts, Hugo J.W.L., Kann, Benjamin H.

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Deep Learning Predicts Lung Cancer Treatment Response from Serial Medical Imaging von Xu, Yiwen, Hosny, Ahmed, Zeleznik, Roman, Parmar, Chintan, Coroller, Thibaud, Franco, Idalid, Mak, Raymond H, Aerts, Hugo J W L

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Revisiting inconsistency in large pharmacogenomic studies [version 3; peer review: 2 approved, 1 approved with reservations] von Safikhani, Zhaleh, Smirnov, Petr, Freeman, Mark, El-Hachem, Nehme, She, Adrian, Rene, Quevedo, Goldenberg, Anna, Birkbak, Nicolai J, Hatzis, Christos, Shi, Leming, Beck, Andrew H, Aerts, Hugo J.W.L, Quackenbush, John, Haibe-Kains, Benjamin

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Computational Radiomics System to Decode the Radiographic Phenotype von van Griethuysen, Joost J M, Fedorov, Andriy, Parmar, Chintan, Hosny, Ahmed, Aucoin, Nicole, Narayan, Vivek, Beets-Tan, Regina G H, Fillion-Robin, Jean-Christophe, Pieper, Steve, Aerts, Hugo J W L

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Outcomes by Tumor Histology and KRAS Mutation Status After Lung Stereotactic Body Radiation Therapy for Early-Stage Non–Small-Cell Lung Cancer von Mak, Raymond H, Hermann, Gretchen, Lewis, John H, Aerts, Hugo J.W.L, Baldini, Elizabeth H, Chen, Aileen B, Colson, Yolonda L, Hacker, Fred H, Kozono, David, Wee, Jon O, Chen, Yu-Hui, Catalano, Paul J, Wong, Kwok-Kin, Sher, David J

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Radiomic-Based Pathological Response Prediction from Primary Tumors and Lymph Nodes in NSCLC von Coroller, Thibaud P., Agrawal, Vishesh, Huynh, Elizabeth, Narayan, Vivek, Lee, Stephanie W., Mak, Raymond H., Aerts, Hugo J.W.L.

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Vulnerabilities of radiomic signature development: The need for safeguards von Welch, Mattea L., McIntosh, Chris, Haibe-Kains, Benjamin, Milosevic, Michael F., Wee, Leonard, Dekker, Andre, Huang, Shao Hui, Purdie, Thomas G., O'Sullivan, Brian, Aerts, Hugo J.W.L., Jaffray, David A.

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Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancer von Rios Velazquez, Emmanuel, Parmar, Chintan, Liu, Ying, Coroller, Thibaud P, Cruz, Gisele, Stringfield, Olya, Ye, Zhaoxiang, Makrigiorgos, Mike, Fennessy, Fiona, Mak, Raymond H, Gillies, Robert, Quackenbush, John, Aerts, Hugo J W L

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CT-based radiomic analysis of stereotactic body radiation therapy patients with lung cancer von Huynh, Elizabeth, Coroller, Thibaud P, Narayan, Vivek, Agrawal, Vishesh, Hou, Ying, Romano, John, Franco, Idalid, Mak, Raymond H, Aerts, Hugo J.W.L

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Radiomic phenotype features predict pathological response in non-small cell lung cancer von Coroller, Thibaud P, Agrawal, Vishesh, Narayan, Vivek, Hou, Ying, Grossmann, Patrick, Lee, Stephanie W, Mak, Raymond H, Aerts, Hugo J.W.L

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Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer von Parmar, Chintan, Leijenaar, Ralph T. H., Grossmann, Patrick, Rios Velazquez, Emmanuel, Bussink, Johan, Rietveld, Derek, Rietbergen, Michelle M., Haibe-Kains, Benjamin, Lambin, Philippe, Aerts, Hugo J.W.L.

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Data Analysis Strategies in Medical Imaging von Parmar, Chintan, Barry, Joseph D, Hosny, Ahmed, Quackenbush, John, Aerts, Hugo J W L

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Radiomics: the process and the challenges von Kumar, Virendra, Gu, Yuhua, Basu, Satrajit, Berglund, Anders, Eschrich, Steven A, Schabath, Matthew B, Forster, Kenneth, Aerts, Hugo J.W.L, Dekker, Andre, Fenstermacher, David, Goldgof, Dmitry B, Hall, Lawrence O, Lambin, Philippe, Balagurunathan, Yoganand, Gatenby, Robert A, Gillies, Robert J

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Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer von Parmar, Chintan, Grossmann, Patrick, Rietveld, Derek, Rietbergen, Michelle M, Lambin, Philippe, Aerts, Hugo J W L

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Deep Learning to Estimate Biological Age From Chest Radiographs von Raghu, Vineet K., Weiss, Jakob, Hoffmann, Udo, Aerts, Hugo J.W.L., Lu, Michael T.

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Current Status and Future Perspectives on Neoadjuvant Therapy in Lung Cancer von Blumenthal, Gideon M., Bunn, Paul A., Chaft, Jamie E., McCoach, Caroline E., Perez, Edith A., Scagliotti, Giorgio V., Carbone, David P., Aerts, Hugo J.W.L., Aisner, Dara L., Bergh, Jonas, Berry, Donald A., Jarkowski, Anthony, Botwood, Nicholas, Cross, Darren A.E., Diehn, Max, Drezner, Nicole L., Doebele, Robert C., Blakely, Collin M., Eberhardt, Wilfried E.E., Felip, Enriqueta, Gianni, Luca, Keller, Steven P., Leavey, Patrick J., Malik, Shakun, Pignatti, Francesco, Prowell, Tatiana M., Redman, Mary W., Rizvi, Naiyer A., Rosell, Rafael, Rusch, Valerie, de Ruysscher, Dirk, Schwartz, Lawrence H., Sridhara, Rajeshwari, Stahel, Rolf A., Swisher, Stephen, Taube, Janis M., Travis, William D., Keegan, Patricia, Wiens, Jacinta R., Wistuba, Ignacio I., Wynes, Murry W., Hirsch, Fred R., Kris, Mark G.

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