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Sarah Jabbour
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2020 – today
- 2024
- [c4]Sarah Jabbour, Gregory Kondas, Ella Kazerooni, Michael W. Sjoding, David Fouhey, Jenna Wiens:
DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks. ECCV (64) 2024: 35-51 - [i4]Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo:
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024) - [i3]Sarah Jabbour, Gregory Kondas, Ella Kazerooni, Michael W. Sjoding, David Fouhey, Jenna Wiens:
DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks. CoRR abs/2407.14509 (2024) - 2023
- [c3]Stefan Hegselmann, Antonio Parziale, Divya Shanmugam, Shengpu Tang, Kristen Severson, Mercy Nyamewaa Asiedu, Serina Chang, Bonaventure F. P. Dossou, Qian Huang, Fahad Kamran, Haoran Zhang, Sujay Nagaraj, Luis Oala, Shan Xu, Chinasa T. Okolo, Helen Zhou, Jessica Dafflon, Caleb Ellington, Sarah Jabbour, Hyewon Jeong, Harry Reyes Nieva, Yuzhe Yang, Ghada Zamzmi, Vishwali Mhasawade, Van Truong, Payal Chandak, Matthew Lee, Peniel Argaw, Kyle Heuton, Harvineet Singh, Thomas Hartvigsen:
Machine Learning for Health (ML4H) 2023. ML4H@NeurIPS 2023: 1-12 - 2022
- [j1]Sarah Jabbour, David Fouhey, Ella Kazerooni, Jenna Wiens, Michael W. Sjoding:
Combining chest X-rays and electronic health record (EHR) data using machine learning to diagnose acute respiratory failure. J. Am. Medical Informatics Assoc. 29(6): 1060-1068 (2022) - [c2]Jiaxuan Wang, Sarah Jabbour, Maggie Makar, Michael W. Sjoding, Jenna Wiens:
Learning Concept Credible Models for Mitigating Shortcuts. NeurIPS 2022 - 2021
- [i2]Sarah Jabbour, David Fouhey, Ella Kazerooni, Jenna Wiens, Michael W. Sjoding:
Combining chest X-rays and EHR data using machine learning to diagnose acute respiratory failure. CoRR abs/2108.12530 (2021) - 2020
- [c1]Sarah Jabbour, David Fouhey, Ella Kazerooni, Michael W. Sjoding, Jenna Wiens:
Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts. MLHC 2020: 750-782 - [i1]Sarah Jabbour, David Fouhey, Ella Kazerooni, Michael W. Sjoding, Jenna Wiens:
Deep Learning Applied to Chest X-Rays: Exploiting and Preventing Shortcuts. CoRR abs/2009.10132 (2020)
Coauthor Index
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