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Do pre-trained deep learning models improve computer-aided classification of digital mammograms?

, , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10575 of SPIE Proceedings, page 1057523. SPIE, (2018)

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Do pre-trained deep learning models improve computer-aided classification of digital mammograms?, , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10575 of SPIE Proceedings, page 1057523. SPIE, (2018)Performance comparison of different loss functions for digital breast tomosynthesis classification using 3D deep learning model., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 11314 of SPIE Proceedings, SPIE, (2020)Implementing PET-guided biopsy: integrating functional imaging data with digital x-ray mammography cameras., , , , , , , , , and . Medical Imaging: Image-Guided Procedures, volume 4319 of SPIE Proceedings, SPIE, (2001)Signal enhancement ratio (SER) quantified from breast DCE-MRI and breast cancer risk., , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9414 of SPIE Proceedings, page 94140M. SPIE, (2015)Deep learning for identifying breast cancer malignancy and false recalls: a robustness study on training strategy., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 10950 of SPIE Proceedings, page 1095005. SPIE, (2019)Deep learning of longitudinal mammogram examinations for breast cancer risk prediction., , , , , and . Pattern Recognit., (2022)