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Sandy Napel

Showing results (91-100 of 113) with videos related to

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European Radiology|September 18, 2009
Computer-aided detection (CAD) of lung nodules in CT scans: radiologist performance and reading time with incremental CAD assistanceJustus E Roos, David Paik, David Olsen, et al.
Oncotarget|September 9, 2017
Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative <sup>18</sup>F FDG-PET/CT metricsRyogo Minamimoto, Mehran Jamali, Olivier Gevaert, et al.
Radiology|May 23, 2006
CT colonography: influence of 3D viewing and polyp candidate features on interpretation with computer-aided detectionRong Shi, Pamela Schraedley-Desmond, Sandy Napel, et al.
Radiology|November 13, 2004
Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detectionGeoffrey D Rubin, John K Lyo, David S Paik, et al.
Scientific Reports|February 1, 2017
Predictive radiogenomics modeling of EGFR mutation status in lung cancerOlivier Gevaert, Sebastian Echegaray, Amanda Khuong, et al.
Translational Oncology|November 13, 2014
NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics SignaturesRivka Colen, Ian Foster, Robert Gatenby, et al.
Radiology|July 26, 2005
Biomedical Imaging Research Opportunities Workshop II: report and recommendationsC Leon Partain, Heang-Ping Chan, Juri G Gelovani, et al.
Communications Medicine|October 31, 2022
Artificial intelligence and machine learning in cancer imagingDow-Mu Koh, Nickolas Papanikolaou, Ulrich Bick, et al.
Neuro-Oncology|September 6, 2021
Machine learning approach to differentiation of peripheral schwannomas and neurofibromas: A multi-center studyMichael Zhang, Elizabeth Tong, Sam Wong, et al.
Cancer Research|May 16, 2018
<i>GFPT2</i>-Expressing Cancer-Associated Fibroblasts Mediate Metabolic Reprogramming in Human Lung AdenocarcinomaWeiruo Zhang, Gina Bouchard, Alice Yu, et al.
Pageof 12

Showing results (91-100 of 113) with videos related to

Sort By:
Pageof 12
European Radiology|September 18, 2009
Computer-aided detection (CAD) of lung nodules in CT scans: radiologist performance and reading time with incremental CAD assistanceJustus E Roos, David Paik, David Olsen, et al.
Oncotarget|September 9, 2017
Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative <sup>18</sup>F FDG-PET/CT metricsRyogo Minamimoto, Mehran Jamali, Olivier Gevaert, et al.
Radiology|May 23, 2006
CT colonography: influence of 3D viewing and polyp candidate features on interpretation with computer-aided detectionRong Shi, Pamela Schraedley-Desmond, Sandy Napel, et al.
Radiology|November 13, 2004
Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detectionGeoffrey D Rubin, John K Lyo, David S Paik, et al.
Scientific Reports|February 1, 2017
Predictive radiogenomics modeling of EGFR mutation status in lung cancerOlivier Gevaert, Sebastian Echegaray, Amanda Khuong, et al.
Translational Oncology|November 13, 2014
NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics SignaturesRivka Colen, Ian Foster, Robert Gatenby, et al.
Radiology|July 26, 2005
Biomedical Imaging Research Opportunities Workshop II: report and recommendationsC Leon Partain, Heang-Ping Chan, Juri G Gelovani, et al.
Communications Medicine|October 31, 2022
Artificial intelligence and machine learning in cancer imagingDow-Mu Koh, Nickolas Papanikolaou, Ulrich Bick, et al.
Neuro-Oncology|September 6, 2021
Machine learning approach to differentiation of peripheral schwannomas and neurofibromas: A multi-center studyMichael Zhang, Elizabeth Tong, Sam Wong, et al.
Cancer Research|May 16, 2018
<i>GFPT2</i>-Expressing Cancer-Associated Fibroblasts Mediate Metabolic Reprogramming in Human Lung AdenocarcinomaWeiruo Zhang, Gina Bouchard, Alice Yu, et al.
Pageof 12