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Daniel L Rubin

Showing results (141-150 of 261) with videos related to

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AMIA ... Annual Symposium Proceedings. AMIA Symposium|November 13, 2008
Web service access to semantic web ontologies for data annotationJoshua D Franklin, José L V Mejino, Landon T Detwiler, et al.
Breast Cancer Research : BCR|September 5, 2018
Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancerJia Wu, Xuejie Li, Xiaodong Teng, et al.
Medical Image Analysis|July 25, 2013
Automated drusen segmentation and quantification in SD-OCT imagesQiang Chen, Theodore Leng, Luoluo Zheng, et al.
Radiology|November 14, 2018
Assessment of Convolutional Neural Networks for Automated Classification of Chest RadiographsJared A Dunnmon, Darvin Yi, Curtis P Langlotz, et al.
Journal of the American College of Radiology : JACR|October 23, 2020
Regulatory Frameworks for Development and Evaluation of Artificial Intelligence-Based Diagnostic Imaging Algorithms: Summary and RecommendationsDavid B Larson, Hugh Harvey, Daniel L Rubin, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|January 24, 2007
Ontology-based representation of simulation models of physiologyDaniel L Rubin, David Grossman, Maxwell Neal, et al.
Computer Methods and Programs in Biomedicine|October 11, 2019
Geographic atrophy segmentation in SD-OCT images using synthesized fundus autofluorescence imagingMenglin Wu, Xinxin Cai, Qiang Chen, et al.
Investigative Radiology|January 1, 2015
Automated classification of usual interstitial pneumonia using regional volumetric texture analysis in high-resolution computed tomographyAdrien Depeursinge, Anne S Chin, Ann N Leung, et al.
Medical Image Analysis|December 1, 2020
An integrated time adaptive geographic atrophy prediction model for SD-OCT imagesYuhan Zhang, Xiwei Zhang, Zexuan Ji, et al.
Journal of Medical Imaging (Bellingham, Wash.)|November 15, 2017
Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imagingImon Banerjee, Sadhika Malladi, Daniela Lee, et al.
Pageof 27

Showing results (141-150 of 261) with videos related to

Sort By:
Pageof 27
AMIA ... Annual Symposium Proceedings. AMIA Symposium|November 13, 2008
Web service access to semantic web ontologies for data annotationJoshua D Franklin, José L V Mejino, Landon T Detwiler, et al.
Breast Cancer Research : BCR|September 5, 2018
Magnetic resonance imaging and molecular features associated with tumor-infiltrating lymphocytes in breast cancerJia Wu, Xuejie Li, Xiaodong Teng, et al.
Medical Image Analysis|July 25, 2013
Automated drusen segmentation and quantification in SD-OCT imagesQiang Chen, Theodore Leng, Luoluo Zheng, et al.
Radiology|November 14, 2018
Assessment of Convolutional Neural Networks for Automated Classification of Chest RadiographsJared A Dunnmon, Darvin Yi, Curtis P Langlotz, et al.
Journal of the American College of Radiology : JACR|October 23, 2020
Regulatory Frameworks for Development and Evaluation of Artificial Intelligence-Based Diagnostic Imaging Algorithms: Summary and RecommendationsDavid B Larson, Hugh Harvey, Daniel L Rubin, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|January 24, 2007
Ontology-based representation of simulation models of physiologyDaniel L Rubin, David Grossman, Maxwell Neal, et al.
Computer Methods and Programs in Biomedicine|October 11, 2019
Geographic atrophy segmentation in SD-OCT images using synthesized fundus autofluorescence imagingMenglin Wu, Xinxin Cai, Qiang Chen, et al.
Investigative Radiology|January 1, 2015
Automated classification of usual interstitial pneumonia using regional volumetric texture analysis in high-resolution computed tomographyAdrien Depeursinge, Anne S Chin, Ann N Leung, et al.
Medical Image Analysis|December 1, 2020
An integrated time adaptive geographic atrophy prediction model for SD-OCT imagesYuhan Zhang, Xiwei Zhang, Zexuan Ji, et al.
Journal of Medical Imaging (Bellingham, Wash.)|November 15, 2017
Assessing treatment response in triple-negative breast cancer from quantitative image analysis in perfusion magnetic resonance imagingImon Banerjee, Sadhika Malladi, Daniela Lee, et al.
Pageof 27