| Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations L Seyyed-Kalantari, H Zhang, M McDermott, IY Chen, M Ghassemi Nature medicine 27 (12), 2176-2182, 2021 | 513 | 2021 |
| AI recognition of patient race in medical imaging: a modelling study JW Gichoya, I Banerjee, AR Bhimireddy, JL Burns, LA Celi, LC Chen, ... The Lancet Digital Health 4 (6), e406-e414, 2022 | 384 | 2022 |
| Hurtful words: quantifying biases in clinical contextual word embeddings H Zhang, AX Lu, M Abdalla, M McDermott, M Ghassemi Proceedings of the ACM Conference on Health, Inference, and Learning, 110-120, 2020 | 197 | 2020 |
| Self-supervised contrastive learning of protein representations by mutual information maximization AX Lu, H Zhang, M Ghassemi, A Moses BioRxiv, 2020.09. 04.283929, 2020 | 98 | 2020 |
| Change is Hard: A Closer Look at Subpopulation Shift Y Yang, H Zhang, D Katabi, M Ghassemi arXiv preprint arXiv:2302.12254, 2023 | 91 | 2023 |
| The road to explainability is paved with bias: Measuring the fairness of explanations A Balagopalan, H Zhang, K Hamidieh, T Hartvigsen, F Rudzicz, ... Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 90 | 2022 |
| Reading Race: AI Recognises Patient's Racial Identity In Medical Images I Banerjee, AR Bhimireddy, JL Burns, LA Celi, LC Chen, R Correa, ... arXiv preprint arXiv:2107.10356, 2021 | 79 | 2021 |
| Improving the Fairness of Chest X-ray Classifiers H Zhang, N Dullerud, K Roth, L Oakden-Rayner, S Pfohl, M Ghassemi Conference on Health, Inference, and Learning, 204-233, 2022 | 72 | 2022 |
| An Empirical Framework for Domain Generalization in Clinical Settings H Zhang, N Dullerud, L Seyyed-Kalantari, Q Morris, S Joshi, M Ghassemi Proceedings of the Conference on Health, Inference, and Learning, 279-290, 2021 | 70 | 2021 |
| An empirical study of representation learning for reinforcement learning in healthcare TW Killian, H Zhang, J Subramanian, M Fatemi, M Ghassemi arXiv preprint arXiv:2011.11235, 2020 | 46 | 2020 |
| A comparison of approaches to improve worst-case predictive model performance over patient subpopulations SR Pfohl, H Zhang, Y Xu, A Foryciarz, M Ghassemi, NH Shah Scientific reports 12 (1), 3254, 2022 | 36 | 2022 |
| The limits of fair medical imaging AI in real-world generalization Y Yang, H Zhang, JW Gichoya, D Katabi, M Ghassemi Nature Medicine, 1-11, 2024 | 26 | 2024 |
| A closer look at auroc and auprc under class imbalance M McDermott, LH Hansen, H Zhang, G Angelotti, J Gallifant arXiv preprint arXiv:2401.06091, 2024 | 23 | 2024 |
| Learning Optimal Predictive Checklists H Zhang, Q Morris, B Ustun, M Ghassemi Advances in Neural Information Processing Systems 34, 2021 | 21 | 2021 |
| "Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts H Zhang, H Singh, M Ghassemi, S Joshi arXiv preprint arXiv:2210.10769, 2022 | 20 | 2022 |
| Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing S Gowda, S Joshi, H Zhang, M Ghassemi Proceedings of the 30th ACM International Conference on Information …, 2021 | 11 | 2021 |
| The Limits of Fair Medical Imaging AI In The Wild Y Yang, H Zhang, JW Gichoya, D Katabi, M Ghassemi arXiv preprint arXiv:2312.10083, 2023 | 8 | 2023 |
| Identifying Transitional High Cost Users from Unstructured Patient Profiles Written by Primary Care Physicians H Zhang, E Candido, AS Wilton, R Duchen, L Jaakkimainen, W Wodchis, ... PACIFIC SYMPOSIUM ON BIOCOMPUTING 2020, 127-138, 2019 | 8 | 2019 |
| Categorizing emails using machine learning with textual features H Zhang, J Rangrej, S Rais, M Hillmer, F Rudzicz, K Malikov Advances in Artificial Intelligence: 32nd Canadian Conference on Artificial …, 2019 | 4 | 2019 |
| Identifying implicit social biases in vision-language models K Hamidieh, H Zhang, W Gerych, T Hartvigsen, M Ghassemi Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7, 547-561, 2024 | 3 | 2024 |
