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Fairness in artificial intelligence models has gained significantly more attention in recent years, especially in the area of medicine, as fairness in medical models is critical to people's well-being and lives.
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Jakub Kuzilek, Martin Hlosta, and Zdenek Zdrahal · 2017
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Zhifei Zhang, Yang Song, and Hairong Qi · 2017
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Alekh Agarwal, Alina Beygelzimer, Miroslav Dudík, John Langford, and Hanna Wallach · 2018
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Julia Dressel and Hany Farid · 2018
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David Madras, Elliot Creager, Toniann Pitassi, and Richard Zemel · 2018
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Fairness definitions explained
Sahil Verma and Julia Rubin · 2018
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Mitigating unwanted biases with adversarial learning
Brian Hu Zhang, Blake Lemoine, and Margaret Mitchell · 2018
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Shiori Sagawa, Pang Wei Koh, Tatsunori B Hashimoto, and Percy Liang · 2019
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Yuji Roh, Kangwook Lee, Steven Whang, and Changho Suh · 2020
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Mhd Hasan Sarhan, Nassir Navab, Abouzar Eslami, and Shadi Albarqouni · 2020
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Yi Zhang and Jitao Sang · 2020
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Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan L Yuille, and Yuyin Zhou · 2021
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Unet++: A nested u-net architecture for medical image segmentation
Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, and Jianming Liang · 2018
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Fair regression: Quantitative definitions and reduction-based algorithms
Alekh Agarwal, Miroslav Dudík, and Zhiwei Steven Wu · 2019
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Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, et al · 2019
Cited alongside, same era.
Mimic-cxr-jpg, a large publicly available database of labeled chest radiographs
Alistair EW Johnson, Tom J Pollard, Nathaniel R Greenbaum, Matthew P Lungren, Chih-ying Deng, Yifan Peng, Zhiyong Lu, Roger G Mark, Seth J Berkowitz, and Steven Horng · 2019
Cited alongside, same era.
Multiaccuracy: Black-box post-processing for fairness in classification
Michael P Kim, Amirata Ghorbani, and James Zou · 2019
Cited alongside, same era.
Bias mitigation post-processing for individual and group fairness
Pranay K Lohia, Karthikeyan Natesan Ramamurthy, Manish Bhide, Diptikalyan Saha, Kush R Varshney, and Ruchir Puri · 2019
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Evaluating deep neural networks trained on clinical images in dermatology with the fitzpatrick 17k dataset
Matthew Groh, Caleb Harris, Luis Soenksen, Felix Lau, Rachel Han, Aerin Kim, Arash Koochek, and Omar Badri · 2021
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Fair attribute classification through latent space de-biasing
Vikram V Ramaswamy, Sunnie SY Kim, and Olga Russakovsky · 2021
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Papila: Dataset with fundus images and clinical data of both eyes of the same patient for glaucoma assessment
Oleksandr Kovalyk, Juan Morales-Sánchez, Rafael Verdú-Monedero, Inmaculada Sellés-Navarro, Ana Palazón-Cabanes, and José-Luis Sancho-Gómez · 2022
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Translation consistent semi-supervised segmentation for 3d medical images
Yuyuan Liu, Yu Tian, Chong Wang, Yuanhong Chen, Fengbei Liu, Vasileios Belagiannis, and Gustavo Carneiro · 2022
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Fair contrastive learning for facial attribute classification
Sungho Park, Jewook Lee, Pilhyeon Lee, Sunhee Hwang, Dohyung Kim, and Hyeran Byun · 2022
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Medfair: Benchmarking fairness for medical imaging
Yongshuo Zong, Yongxin Yang, and Timothy Hospedales · 2022
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Equitable artificial intelligence for glaucoma screening with fair identity normalization
Min Shi, Yan Luo, Yu Tian, Lucy Q Shen, Tobias Elze, Nazlee Zebardast, Mohammad Eslami, Saber Kazeminasab, Michael V Boland, David S Friedman, et al · 2023
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Customized segment anything model for medical image segmentation
Kaidong Zhang and Dong Liu · 2023
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