Seyyed-Kalantari, Laleh

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

Seyyed-Kalantari, L., Zhang, H., McDermott, M. B. A., Chen, I. Y., & Ghassemi, M. (2021) · Nature Medicine

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 928

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

Gichoya, J. W., Banerjee, I., Bhimireddy, A. R., Burns, J. L., Celi, L. A., Chen, L.-C., Correa, R., Dullerud, N., Ghassemi, M., Huang, S.-C., et al. (2022) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 611

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

Gichoya, J. W., Thomas, K., Celi, L. A., Safdar, N., Banerjee, I., Banja, J. D., Seyyed-Kalantari, L., Trivedi, H., & Purkayastha, S. (2023) · The British Journal of Radiology

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 277

CheXclusion: Fairness gaps in deep chest X-ray classifiers

Seyyed-Kalantari, L., Liu, G., McDermott, M., Chen, I. Y., & Ghassemi, M. (2020) · Biocomputing 2021

Artificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

Cited by 275

The Subgroup Imperative: Chest Radiograph Classifier Generalization Gaps in Patient, Setting, and Pathology Subgroups

Ahluwalia, M., Abdalla, M., Sanayei, J., Seyyed-Kalantari, L., Hussain, M., Ali, A., & Fine, B. (2023) · Radiology: Artificial Intelligence

Artificial Intelligence in Healthcare and EducationCOVID-19 diagnosis using AI

Cited by 26