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Radiology|February 4, 2025
Using AI to Select Women with Intermediate Breast Cancer Risk for Breast Screening with MRISuzanne L van Winkel, Riccardo Samperna, Elizabeth A Loehrer, et al.European Radiology|June 12, 2025
Breast cancer in women after withdrawing from an increased-risk MRI screening programSuzanne L van Winkel, Riccardo Samperna, Elizabeth A Loehrer, et al.Magnetic Resonance Imaging Clinics of North America|May 25, 2010
The effectiveness of MR imaging in the assessment of invasive lobular carcinoma of the breastRitse M MannEuropean Radiology|May 5, 2021
Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case studySuzanne L van Winkel, Alejandro Rodríguez-Ruiz, Linda Appelman, et al.Diagnostics (Basel, Switzerland)|June 26, 2025
An Exploration of Discrepant Recalls Between AI and Human Readers of Malignant Lesions in Digital Mammography ScreeningSuzanne L van Winkel, Ioannis Sechopoulos, Alejandro Rodríguez-Ruiz, et al.The Lancet. Digital Health|August 15, 2025
AI as an independent second reader in detection of clinically relevant breast cancers within a population-based screening programme in the Netherlands: a retrospective cohort studySuzanne L van Winkel, Jim Peters, Natasja Janssen, et al.Radiologic Clinics of North America|May 22, 2024
Contrast-enhanced Mammography versus MR Imaging of the BreastRitse M Mann, Valentina LongoBreast (Edinburgh, Scotland)|January 14, 2020
Stand-alone artificial intelligence - The future of breast cancer screening?Ioannis Sechopoulos, Ritse M MannJournal of Magnetic Resonance Imaging : JMRI|January 24, 2025
Breast MRI to Screen Women With Extremely Dense BreastsCarla Sitges, Ritse M MannSeminars in Nuclear Medicine|March 27, 2022
Application of Deep Learning in Breast Cancer ImagingLuuk Balkenende, Jonas Teuwen, Ritse M MannPageof 16