1. Weina Jin, Mostafa Fatehi, Ru Guo, and Ghassan Hamarneh. Evaluating the Clinical Utility of Artificial Intelligence Assistance and its Explanation on the Glioma Grading Task (Jin and Fatehi: Joint first authors). Artificial Intelligence In Medicine, 000(000):000-000, 2023. Keyword(s): Deep Learning, Explainable AI (XAI). [bibtex-key = aiim2023]



2. Weina Jin, Xiaoxiao Li, Mostafa Fatehi, and Ghassan Hamarneh. Generating Post-Hoc Explanation from Deep Neural Networks for Multi-Modal Medical Image Analysis Tasks. MethodX, 10(102009):1-7, 2023. Keyword(s): Deep Learning, Explainable AI (XAI), Multimodal, Software and Tools. [bibtex-key = methodx2023]



3. Weina Jin, Xiaoxiao Li, Mostafa Fatehi, and Ghassan Hamarneh. Guidelines and evaluation for clinical explainable AI in medical image analysis. Medical Image Analysis (MedIA), 102684:1-30, 2022. Keyword(s): Deep Learning, Explainable AI (XAI), Multimodal. [bibtex-key = media2022b]

1. Elise Li Zheng, Weina Jin, Ghassan Hamarneh, and Sandra Soo-Jin Lee. What does “explainable” AI explain? Power dynamics and AI explainability in precision medicine. In Congress on Ethical, Legal, and Social Implications (ELSI): AI and machine learning | Equity and justice in genetics | Precision Medicine, 2024. Keyword(s): Explainable AI, Ethical AI, Societal Implications of AI. [bibtex-key = elsi2024]



2. Weina Jin, Xiaoxiao Li, and Ghassan Hamarneh. Evaluating Explainable AI on Multi-Modal Medical Imaging Task: Can Existing Algorithms Fulfill Clinical Requirements?. In Association for the Advancement of Artificial Intelligence Conference (AAAI), volume 36, pages 11945-11953, 2022. Keyword(s): Deep Learning, Explainable AI (XAI), Glioma Imaging, Machine Learning, MRI, Multimodal. [bibtex-key = aaai2022]



3. Weina Jin and Ghassan Hamarneh. Physician-Centered Explainable AI. In Biomedical Imaging and Artificial Intelligence (BMIAI) cluster Fall Research Showcase, Vancouver, Canada, pages 1, 2021. Keyword(s): Deep Learning, Explainable AI (XAI), Glioma Imaging. [bibtex-key = bmiai2021c]



4. Weina Jin, Xiaoxiao Li, and Ghassan Hamarneh. One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images. In International Conference on Machine Learning (ICML) workshop on Interpretable Machine Learning in Healthcare (IMLH), pages 1-13, 2021. Keyword(s): Deep Learning, Explainable AI (XAI), Glioma Imaging, Multimodal. [bibtex-key = icml_imlh2021]



5. Weina Jin, Sheelagh Carpendale, Ghassan Hamarneh, and Diane Gromala. Bridging AI Developers and End Users: an End-User-Centred Explainable AI Taxonomy and Visual Vocabularies. In IEEE Visualization (IEEE Vis), 2019. Keyword(s): Explainable AI (XAI), Deep Learning, User Interaction, Visualization. [bibtex-key = vis2019]

1. Weina Jin, Jianyu Fan, Diane Gromala, Philippe Pasquier, and Ghassan Hamarneh. Invisible Users: Uncovering End-Users' Requirements for Explainable AI via Explanation Forms and Goals. Technical report arxiv.2302.06609, 2 2023. Keyword(s): Deep Learning, Explainable AI (XAI), Multimodal, Software and Tools. [bibtex-key = arxiv:2302.06609]



2. Weina Jin, Xiaoxiao Li, and Ghassan Hamarneh. The XAI Alignment Problem: Rethinking How Should We Evaluate Human-Centered AI Explainability Techniques. Technical report arxiv.2303.17707, 4 2023. Keyword(s): Explainable AI (XAI). [bibtex-key = arxiv:2303.17707]



3. Weina Jin, Jianyu Fan, Diane Gromala, Philippe Pasquier, and Ghassan Hamarneh. EUCA: the End-User-Centered Explainable AI Framework. Technical report arXiv:2102.02437, 2 2022. Keyword(s): Explainable AI (XAI). [bibtex-key = arxiv:2102.02437]



4. Weina Jin, Jianyu Fan, Diane Gromala, Philippe Pasquier, Xiaoxiao Li, and Ghassan Hamarneh. Transcending XAI Algorithm Boundaries through End-User-Inspired Design. Technical report arXiv:2208.08739, 8 2022. Keyword(s): Deep Learning, Explainable AI (XAI), Multimodal. [bibtex-key = arxiv:2208.08739]



5. Weina Jin, Mostafa Fatehi, Ru Guo, and Ghassan Hamarneh. Evaluating the Clinical Utility of Artificial Intelligence Assistance and its Explanation on Glioma Grading Task. Technical report medRxiv 2022.12.07.22282726, December 2022. Keyword(s): Deep Learning, Explainable AI (XAI), Multimodal. [bibtex-key = medrxiv2022_22282726]



6. Weina Jin, Xiaoxiao Li, Mostafa Fatehi, and Ghassan Hamarneh. Guidelines and evaluation for clinical explainable AI on medical image analysis. Technical report arXiv:2202.10553, 2 2022. Keyword(s): Deep Learning, Explainable AI (XAI). [bibtex-key = arxiv:2202.10553]



7. Weina Jin, Xiaoxiao Li, and Ghassan Hamarneh. Evaluating Explainable AI on a Multi-Modal Medical Imaging Task: Can Existing Algorithms Fulfill Clinical Requirements?. Technical report arXiv:2203.06487, 3 2022. Keyword(s): Deep Learning, Explainable AI (XAI), Multimodal. [bibtex-key = arxiv:2203.06487]

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All person copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

This document was translated from BibT_EX by bibtex2html