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2020 – today
- 2024
[i8]Julia Yang, Alina Jade Barnett, Jon Donnelly, Satvik Kishore, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin:
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography. CoRR abs/2406.06386 (2024)- [i7]Frank Willard, Luke Moffett, Emmanuel Mokel, Jon Donnelly, Stark Guo, Julia Yang, Giyoung Kim, Alina Jade Barnett, Cynthia Rudin:
This Looks Better than That: Better Interpretable Models with ProtoPNeXt. CoRR abs/2406.14675 (2024) - 2023
- [b1]Alina Jade Barnett:
Interpretable Machine Learning With Medical Applications. Duke University, Durham, NC, USA, 2023 - [c5]Yanchen Jessie Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz
, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin:
A user interface to communicate interpretable AI decisions to radiologists. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - [c4]Yanchen Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin:
A user interface to communicate interpretable AI decisions to radiologists (Erratum). Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - [i6]Dennis Tang, Frank Willard, Ronan Tegerdine, Luke Triplett, Jon Donnelly, Luke Moffett, Lesia Semenova, Alina Jade Barnett, Jin Jing, Cynthia Rudin, M. Brandon Westover:
ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges. CoRR abs/2312.10056 (2023) - 2022
- [c3]Jon Donnelly, Alina Jade Barnett, Chaofan Chen:
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes. CVPR 2022: 10255-10265 - [c2]Alina Jade Barnett, Vaibhav Sharma, Neel Gajjar, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin:
Interpretable deep learning models for better clinician-AI communication in clinical mammography. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [i5]Alina Jade Barnett, Zhicheng Guo, Jin Jing, Wendong Ge, Cynthia Rudin, M. Brandon Westover:
Mapping the Ictal-Interictal-Injury Continuum Using Interpretable Machine Learning. CoRR abs/2211.05207 (2022) - 2021
- [j1]Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin:
A case-based interpretable deep learning model for classification of mass lesions in digital mammography. Nat. Mach. Intell. 3(12): 1061-1070 (2021) - [i4]Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin:
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography. CoRR abs/2103.12308 (2021) - [i3]Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin:
Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning. CoRR abs/2107.05605 (2021) - [i2]Jon Donnelly, Alina Jade Barnett, Chaofan Chen:
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes. CoRR abs/2111.15000 (2021)
2010 – 2019
- 2019
- [c1]Chaofan Chen, Oscar Li, Daniel Tao, Alina Barnett, Cynthia Rudin, Jonathan Su:
This Looks Like That: Deep Learning for Interpretable Image Recognition. NeurIPS 2019: 8928-8939 - 2018
- [i1]Chaofan Chen, Oscar Li, Alina Barnett, Jonathan Su, Cynthia Rudin:
This looks like that: deep learning for interpretable image recognition. CoRR abs/1806.10574 (2018)
Coauthor Index
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