| 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 | 1857 | 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 | 223* | 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 | 213 | 2022 |
| 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 | 49 | 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 | 31 | 2024 |
| 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 | 25 | 2021 |
| 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 | 19 | 2024 |
| 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, 2019 | 14 | 2019 |
| Rashomon sets for prototypical-part networks: Editing interpretable models in real-time J Donnelly, Z Guo, AJ Barnett, H McTavish, C Chen, C Rudin Proceedings of the Computer Vision and Pattern Recognition Conference, 4528-4538, 2025 | 9 | 2025 |
| 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 | 6 | 2022 |
| 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 | 5 | 2023 |
| 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 | 4 | 2023 |
| 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 | 3 | 2024 |
| 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 | 3 | 2022 |
| 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 | 1 | 2023 |
| An Interpretable Machine Learning System to Identify 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 |
| It's LIT! Reliability-Optimized LLMs with Inspectable Tools R Zhang, J Donnelly, Z Guo, G Khalighinejad, H Huang, AJ Barnett, ... arXiv preprint arXiv:2511.14903, 2025 | | 2025 |
| This EEG Looks Like These EEGs: Interpretable Interictal Epileptiform Discharge Detection With ProtoEEG-kNN D Tang, J Donnelly, AJ Barnett, L Semenova, J Jing, P Hadar, I Karakis, ... International Conference on Medical Image Computing and Computer-Assisted …, 2025 | | 2025 |
| Multi-site validation of an interpretable model to analyze breast masses L Moffett, AJ Barnett, J Donnelly, FR Schwartz, H Trivedi, J Lo, C Rudin PloS one 20 (6), e0320091, 2025 | | 2025 |
| Improving annotation efficiency for fully labeling a breast mass segmentation dataset V Sharma, AJ Barnett, J Yang, S Cheon, G Kim, F Regina Schwartz, ... Journal of Medical Imaging 12 (3), 035501-035501, 2025 | | 2025 |
Cynthia RudinProfessor of Computer Science, ECE, Statistics, and Biostatistics & Bioinformatics, Duke UniversityVerified email at cs.duke.edu
