Alina Barnett

According to our database, Alina Barnett authored at least 14 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

This Looks Better than That: Better Interpretable Models with ProtoPNeXt.

Frank Willard, Luke Moffett, Emmanuel Mokel, Jon Donnelly, Stark Guo, Julia Yang, Giyoung Kim, Alina Jade Barnett, Cynthia Rudin

CoRR, 2024

FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography.

Julia Yang, Alina Jade Barnett, Jon Donnelly, Satvik Kishore, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Interpretable Machine Learning With Medical Applications.

Alina Jade Barnett

PhD thesis, 2023

ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges.

Dennis Tang, Frank Willard, Ronan Tegerdine, Luke Triplett, Jon Donnelly, Luke Moffett, Lesia Semenova, Alina Jade Barnett, Jin Jing, Cynthia Rudin, M. Brandon Westover

CoRR, 2023

A user interface to communicate interpretable AI decisions to radiologists (Erratum).

Yanchen Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin

Proceedings of the Medical Imaging 2023: Image Perception, 2023

A user interface to communicate interpretable AI decisions to radiologists.

Yanchen Jessie Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin

Proceedings of the Medical Imaging 2023: Image Perception, 2023

2022

Mapping the Ictal-Interictal-Injury Continuum Using Interpretable Machine Learning.

Alina Jade Barnett, Zhicheng Guo, Jin Jing, Wendong Ge, Cynthia Rudin, M. Brandon Westover

CoRR, 2022

Interpretable deep learning models for better clinician-AI communication in clinical mammography.

Alina Jade Barnett, Vaibhav Sharma, Neel Gajjar, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin

Proceedings of the Medical Imaging 2022: Image Perception, 2022

Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes.

Jon Donnelly, Alina Jade Barnett, Chaofan Chen

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

A case-based interpretable deep learning model for classification of mass lesions in digital mammography.

Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin

Nat. Mach. Intell., 2021

Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning.

Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin

CoRR, 2021

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

Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin

CoRR, 2021

2019

This Looks Like That: Deep Learning for Interpretable Image Recognition.

Chaofan Chen, Oscar Li, Daniel Tao, Alina Barnett, Cynthia Rudin, Jonathan Su

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

This looks like that: deep learning for interpretable image recognition.

Chaofan Chen, Oscar Li, Alina Barnett, Jonathan Su, Cynthia Rudin

CoRR, 2018