Haoran Zhang

Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations

2021 · 713 Zit. · Nature Medicine

AI recognition of patient race in medical imaging: a modelling study

2022 · 483 Zit. · The Lancet Digital Health

Hurtful words

2020 · 120 Zit.

The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations

2022 · 63 Zit. · 2022 ACM Conference on Fairness, Accountability, and Transparency

Reading Race: AI Recognises Patient's Racial Identity In Medical Images

2021 · 31 Zit. · arXiv (Cornell University)

Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings

2020 · 29 Zit. · arXiv (Cornell University)

ChatGPT’s ability to generate realistic experimental images poses a new challenge to academic integrity

2024 · 24 Zit. · Journal of Hematology & Oncology

Change is Hard: A Closer Look at Subpopulation Shift

2023 · 11 Zit. · arXiv (Cornell University)

Improving the Fairness of Chest X-ray Classifiers

2022 · 10 Zit. · arXiv (Cornell University)

Reply to: ‘Potential sources of dataset bias complicate investigation of underdiagnosis by machine learning algorithms’ and ‘Confounding factors need to be accounted for in assessing bias by machine learning algorithms’

2022 · 5 Zit. · Nature Medicine

Algorithmic Fairness in Chest X-ray Diagnosis: A Case Study

2023 · 3 Zit.