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Justin Szeto
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2020 – today
- 2025
[c4]Xing Shen
, Justin Szeto, Mingyang Li, Hengguan Huang, Tal Arbel:
Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification. MICCAI (7) 2025: 226-236
[i11]Xing Shen, Justin Szeto, Mingyang Li, Hengguan Huang, Tal Arbel:
Exposing and Mitigating Calibration Biases and Demographic Unfairness in MLLM Few-Shot In-Context Learning for Medical Image Classification. CoRR abs/2506.23298 (2025)
[i10]Gian Mario Favero, Ge Ya Luo, Nima Fathi, Justin Szeto, Douglas L. Arnold, Brennan Nichyporuk, Chris Pal, Tal Arbel:
Spatio-Temporal Conditional Diffusion Models for Forecasting Future Multiple Sclerosis Lesion Masks Conditioned on Treatments. CoRR abs/2508.07006 (2025)
[i9]Emily Kaczmarek, Justin Szeto, Brennan Nichyporuk, Tal Arbel:
SSL-AD: Spatiotemporal Self-Supervised Learning for Generalizability and Adaptability Across Alzheimer's Prediction Tasks and Datasets. CoRR abs/2509.10453 (2025)
[i8]Emily Kaczmarek, Justin Szeto, Brennan Nichyporuk, Tal Arbel:
Building a General SimCLR Self-Supervised Foundation Model Across Neurological Diseases to Advance 3D Brain MRI Diagnoses. CoRR abs/2509.10620 (2025)- 2023
[c3]Changjian Shui, Justin Szeto, Raghav Mehta, Douglas L. Arnold, Tal Arbel:
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. MICCAI (3) 2023: 189-198
[i7]Changjian Shui, Justin Szeto, Raghav Mehta, Douglas L. Arnold, Tal Arbel:
Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis. CoRR abs/2307.01738 (2023)
[i6]Eric Zimmermann, Justin Szeto, Frédéric Ratle:
An Empirical Study of Uncertainty in Polygon Annotation and the Impact of Quality Assurance. CoRR abs/2311.02707 (2023)
[i5]Eric Zimmermann, Justin Szeto, Jérôme Pasquero, Frédéric Ratle:
Benchmarking a Benchmark: How Reliable is MS-COCO? CoRR abs/2311.02709 (2023)- 2022
[i4]Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Jean-Pierre R. Falet, Douglas L. Arnold, Sotirios A. Tsaftaris, Tal Arbel:
Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation. CoRR abs/2210.17398 (2022)- 2021
[c2]Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Sotirios A. Tsaftaris, Douglas L. Arnold, Tal Arbel:
Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation. DART/FAIR@MICCAI 2021: 101-111
[c1]Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Nazanin Mohammadi Sepahvand, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent:
Accounting for Variance in Machine Learning Benchmarks. MLSys 2021
[i3]Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi, Assya Trofimov, Brennan Nichyporuk, Justin Szeto, Naz Sepah, Edward Raff, Kanika Madan, Vikram Voleti, Samira Ebrahimi Kahou, Vincent Michalski, Dmitriy Serdyuk, Tal Arbel, Chris Pal, Gaël Varoquaux, Pascal Vincent:
Accounting for Variance in Machine Learning Benchmarks. CoRR abs/2103.03098 (2021)
[i2]Brennan Nichyporuk, Justin Szeto, Douglas L. Arnold, Tal Arbel:
Optimizing Operating Points for High Performance Lesion Detection and Segmentation Using Lesion Size Reweighting. CoRR abs/2107.12978 (2021)
[i1]Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Sotirios A. Tsaftaris, Douglas L. Arnold, Tal Arbel:
Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation. CoRR abs/2108.00713 (2021)
Coauthor Index

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last updated on 2025-11-20 22:23 CET by the dblp team
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