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IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography.

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IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography., , , , , , and . CoRR, (2021)A user interface to communicate interpretable AI decisions to radiologists., , , , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)Mapping the Ictal-Interictal-Injury Continuum Using Interpretable Machine Learning., , , , , and . CoRR, (2022)Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes., , and . CVPR, page 10255-10265. IEEE, (2022)Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes., , and . CoRR, (2021)ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges., , , , , , , , , and 1 other author(s). CoRR, (2023)Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning., , , , , , and . CoRR, (2021)Interpretable deep learning models for better clinician-AI communication in clinical mammography., , , , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12035 of SPIE Proceedings, SPIE, (2022)Interpretable Machine Learning With Medical Applications.. Duke University, Durham, NC, USA, (2023)base-search.net (ftdukeunivdsp:oai:localhost:10161/29171).A case-based interpretable deep learning model for classification of mass lesions in digital mammography., , , , , , and . Nat. Mach. Intell., 3 (12): 1061-1070 (2021)