| This looks like that: deep learning for interpretable image recognition C Chen, O Li, D Tao, A Barnett, C Rudin, JK Su Advances in neural information processing systems 32, 2019 | 1205 | 2019 |
| A case-based interpretable deep learning model for classification of mass lesions in digital mammography AJ Barnett, FR Schwartz, C Tao, C Chen, Y Ren, JY Lo, C Rudin Nature Machine Intelligence 3 (12), 1061-1070, 2021 | 125* | 2021 |
| Deformable protopnet: An interpretable image classifier using deformable prototypes J Donnelly, AJ Barnett, C Chen Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 108 | 2022 |
| Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning AJ Barnett, FR Schwartz, C Tao, C Chen, Y Ren, JY Lo, C Rudin Deep Learning, Case-Based Reasoning, and AutoML: Present and Future …, 2021 | 15 | 2021 |
| This looks like that: Deep learning for interpretable image recognition. arXiv C Chen, O Li, C Tao, AJ Barnett, J Su, C Rudin arXiv preprint arXiv:1806.10574, 2018 | 11 | 2018 |
| AsymMirai: Interpretable Mammography-based Deep Learning Model for 1–5-year Breast Cancer Risk Prediction J Donnelly, L Moffett, AJ Barnett, H Trivedi, F Schwartz, J Lo, C Rudin Radiology 310 (3), e232780, 2024 | 5 | 2024 |
| A user interface to communicate interpretable AI decisions to radiologists YJ Ou, AJ Barnett, A Mitra, FR Schwartz, C Chen, L Grimm, JY Lo, ... Medical Imaging 2023: Image Perception, Observer Performance, and Technology …, 2023 | 3 | 2023 |
| Interpretable deep learning models for better clinician-AI communication in clinical mammography AJ Barnett, V Sharma, N Gajjar, J Fang, F Schwartz, C Chen, JY Lo, ... Medical Imaging 2022: Image Perception, Observer Performance, and Technology …, 2022 | 3 | 2022 |
| Mapping the ictal-interictal-injury continuum using interpretable machine learning AJ Barnett, Z Guo, J Jing, W Ge, C Rudin, MB Westover arXiv preprint arXiv:2211.05207 2, 2022 | 2 | 2022 |
| Interpretable machine learning system to eeg patterns on the ictal-interictal-injury continuum AJ Barnett, Z Guo, J Jing, W Ge, C Rudin, MB Westover arXiv preprint arXiv:2211.05207, 2022 | 1 | 2022 |
| This Looks Better than That: Better Interpretable Models with ProtoPNeXt F Willard, L Moffett, E Mokel, J Donnelly, S Guo, J Yang, G Kim, AJ Barnett, ... arXiv preprint arXiv:2406.14675, 2024 | | 2024 |
| Improving Clinician Performance in Classifying EEG Patterns on the Ictal–Interictal Injury Continuum Using Interpretable Machine Learning AJ Barnett, Z Guo, J Jing, W Ge, PW Kaplan, WY Kong, I Karakis, ... NEJM AI 1 (6), AIoa2300331, 2024 | | 2024 |
| FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography J Yang, AJ Barnett, J Donnelly, S Kishore, J Fang, FR Schwartz, C Chen, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
| ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges D Tang, F Willard, R Tegerdine, L Triplett, J Donnelly, L Moffett, ... arXiv preprint arXiv:2312.10056, 2023 | | 2023 |
| A user interface to communicate interpretable AI decisions to radiologists (Erratum) Y Ou, AJ Barnett, A Mitra, FR Schwartz, C Chen, LJ Grimm, JY Lo, ... Medical Imaging 2023: Image Perception, Observer Performance, and Technology …, 2023 | | 2023 |
| Interpretable Machine Learning With Medical Applications AJ Barnett Duke University, 2023 | | 2023 |
| Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes (Supplement) J Donnelly, AJ Barnett, C Chen | | |
Cynthia RudinProfessor of Computer Science, ECE, Statistics, and Biostatistics & Bioinformatics, Duke UniversityPotvrđena adresa e-pošte na cs.duke.edu
