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Global mammographic radiomic signature can predict radiologists' difficult-to-interpret normal cases.

, , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)

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Global Radiomic Features from Mammography for Predicting Difficult-To-Interpret Normal Cases., , , and . J. Digit. Imaging, 36 (4): 1541-1552 (August 2023)An end-to-end deep learning model can detect the gist of the abnormal in prior mammograms as perceived by experienced radiologists., , , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11599 of SPIE Proceedings, SPIE, (2021)The reliability of radiologists' first impression interpreting a screening mammogram., , , , , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12035 of SPIE Proceedings, SPIE, (2022)False-negative diagnosis might occur due to absence of the global radiomic signature of malignancy on screening mammograms., , , , , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)Investigating the error-making patterns in reading high-density screening mammograms between radiologists from two countries., , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)Global mammographic radiomic signature can predict radiologists' difficult-to-interpret normal cases., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)