Judy Wawira Gichoya

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

2022 · 465 Zit. · The Lancet Digital Health

Assessing the potential of GPT-4 to perpetuate racial and gender biases in health care: a model evaluation study

2023 · 403 Zit. · The Lancet Digital Health

Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement

2019 · 340 Zit. · Radiology

Ethics of large language models in medicine and medical research

2023 · 265 Zit. · The Lancet Digital Health

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update

2024 · 243 Zit. · Radiology Artificial Intelligence

The TRIPOD-LLM reporting guideline for studies using large language models

2025 · 221 Zit. · Nature Medicine

AI pitfalls and what not to do: mitigating bias in AI

2023 · 214 Zit. · British Journal of Radiology

The limits of fair medical imaging AI in real-world generalization

2024 · 167 Zit. · Nature Medicine

Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment

2023 · 114 Zit. · Journal of Medical Imaging

Ethics of artificial intelligence in radiology: summary of the joint European and North American multisociety statement

2019 · 114 Zit. · Insights into Imaging

Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement

2019 · 112 Zit. · Canadian Association of Radiologists Journal

Decoding radiology reports: Potential application of OpenAI ChatGPT to enhance patient understanding of diagnostic reports

2023 · 111 Zit. · Clinical Imaging

Equity in essence: a call for operationalising fairness in machine learning for healthcare

2021 · 104 Zit. · BMJ Health & Care Informatics

Ethics of Artificial Intelligence in Radiology: Summary of the Joint European and North American Multisociety Statement

2019 · 92 Zit. · Journal of the American College of Radiology

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

2024 · 84 Zit. · The Lancet Digital Health