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Adam E Flanders

Showing results (101-110 of 130) with videos related to

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Neurosurgical Focus|August 8, 2023
Radiomic signatures of meningiomas using the Ki-67 proliferation index as a prognostic marker of clinical outcomesOmaditya Khanna, Anahita Fathi Kazerooni, Sherjeel Arif, et al.
Radiology. Artificial Intelligence|March 13, 2024
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI ChallengesFelipe C Kitamura, Luciano M Prevedello, Errol Colak, et al.
Radiology|November 28, 2018
The RSNA Pediatric Bone Age Machine Learning ChallengeSafwan S Halabi, Luciano M Prevedello, Jayashree Kalpathy-Cramer, et al.
Cancer|March 5, 2020
Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastomaHamed Akbari, Saima Rathore, Spyridon Bakas, et al.
AJR. American Journal of Roentgenology|May 27, 2026
Measuring Radiology's Impact: Core Concepts for Tracking Patient-Oriented Outcomes and Delivering High-Value Care-A Perspective by the ACR's Relevance and Impact CommitteeAlexander M McKinney, Thiago A Braga, John E Jordan, et al.
Journal of Neuroradiology = Journal De Neuroradiologie|July 7, 2014
Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patientsManal Nicolasjilwan, Ying Hu, Chunhua Yan, et al.
Spine|November 21, 2009
Injury of the posterior ligamentous complex of the thoracolumbar spine: a prospective evaluation of the diagnostic accuracy of magnetic resonance imagingAlexander R Vaccaro, Jeffrey A Rihn, Davor Saravanja, et al.
Radiology. Artificial Intelligence|May 3, 2021
Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage ChallengeAdam E Flanders, Luciano M Prevedello, George Shih, et al.
Radiology. Artificial Intelligence|May 3, 2021
Erratum: Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage ChallengeAdam E Flanders, Luciano M Prevedello, George Shih, et al.
Nature Communications|July 7, 2023
Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographsAyis Pyrros, Stephen M Borstelmann, Ramana Mantravadi, et al.
Pageof 13

Showing results (101-110 of 130) with videos related to

Sort By:
Pageof 13
Neurosurgical Focus|August 8, 2023
Radiomic signatures of meningiomas using the Ki-67 proliferation index as a prognostic marker of clinical outcomesOmaditya Khanna, Anahita Fathi Kazerooni, Sherjeel Arif, et al.
Radiology. Artificial Intelligence|March 13, 2024
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI ChallengesFelipe C Kitamura, Luciano M Prevedello, Errol Colak, et al.
Radiology|November 28, 2018
The RSNA Pediatric Bone Age Machine Learning ChallengeSafwan S Halabi, Luciano M Prevedello, Jayashree Kalpathy-Cramer, et al.
Cancer|March 5, 2020
Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastomaHamed Akbari, Saima Rathore, Spyridon Bakas, et al.
AJR. American Journal of Roentgenology|May 27, 2026
Measuring Radiology's Impact: Core Concepts for Tracking Patient-Oriented Outcomes and Delivering High-Value Care-A Perspective by the ACR's Relevance and Impact CommitteeAlexander M McKinney, Thiago A Braga, John E Jordan, et al.
Journal of Neuroradiology = Journal De Neuroradiologie|July 7, 2014
Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patientsManal Nicolasjilwan, Ying Hu, Chunhua Yan, et al.
Spine|November 21, 2009
Injury of the posterior ligamentous complex of the thoracolumbar spine: a prospective evaluation of the diagnostic accuracy of magnetic resonance imagingAlexander R Vaccaro, Jeffrey A Rihn, Davor Saravanja, et al.
Radiology. Artificial Intelligence|May 3, 2021
Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage ChallengeAdam E Flanders, Luciano M Prevedello, George Shih, et al.
Radiology. Artificial Intelligence|May 3, 2021
Erratum: Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage ChallengeAdam E Flanders, Luciano M Prevedello, George Shih, et al.
Nature Communications|July 7, 2023
Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographsAyis Pyrros, Stephen M Borstelmann, Ramana Mantravadi, et al.
Pageof 13