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Radiology. Artificial Intelligence|November 6, 2024
RSNA 2023 Abdominal Trauma AI Challenge: Review and OutcomesSebastiaan Hermans, Zixuan Hu, Robyn L Ball, et al.
IEEE Transactions on Bio-Medical Engineering|July 27, 2010
An integrative approach for in silico glioma researchLee A D Cooper, Jun Kong, David A Gutman, et al.
Neurosurgery|August 30, 2021
Machine Learning Using Multiparametric Magnetic Resonance Imaging Radiomic Feature Analysis to Predict Ki-67 in World Health Organization Grade I MeningiomasOmaditya Khanna, Anahita Fathi Kazerooni, Christopher J Farrell, et al.
Stroke|March 4, 2006
Perfusion-CT assessment of infarct core and penumbra: receiver operating characteristic curve analysis in 130 patients suspected of acute hemispheric strokeMax Wintermark, Adam E Flanders, Birgitta Velthuis, et al.
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.
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