| Underdiagnosis bias of artificial intelligence algorithms applied to chest radiographs in under-served patient populations L Seyyed-Kalantari, H Zhang, MBA McDermott, IY Chen, M Ghassemi Nature medicine 27 (12), 2176-2182, 2021 | 893 | 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 | 624 | 2022 |
| CheXclusion: Fairness gaps in deep chest X-ray classifiers L Seyyed-Kalantari, G Liu, M McDermott, IY Chen, M Ghassemi BIOCOMPUTING 2021: proceedings of the Pacific symposium, 232-243, 2020 | 428 | 2020 |
| AI pitfalls and what not to do: mitigating bias in AI JW Gichoya, K Thomas, LA Celi, N Safdar, I Banerjee, JD Banja, ... The British Journal of Radiology 96 (1150), 20230023, 2023 | 280 | 2023 |
| “Shortcuts” causing bias in radiology artificial intelligence: causes, evaluation, and mitigation I Banerjee, K Bhattacharjee, JL Burns, H Trivedi, S Purkayastha, ... Journal of the American College of Radiology 20 (9), 842-851, 2023 | 120 | 2023 |
| 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 | 94 | 2021 |
| 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 | 80 | 2021 |
| Evaluating knowledge transfer in the neural network for medical images S Akbarian, L Seyyed-Kalantari, F Khalvati, E Dolatabadi IEEE Access 11, 85812-85821, 2023 | 31 | 2023 |
| The subgroup imperative: chest radiograph classifier generalization gaps in patient, setting, and pathology subgroups M Ahluwalia, M Abdalla, J Sanayei, L Seyyed-Kalantari, M Hussain, A Ali, ... Radiology: Artificial Intelligence 5 (5), e220270, 2023 | 29 | 2023 |
| Wideband cloaking of objects with arbitrary shapes exploiting adjoint sensitivities LS Kalantari, MH Bakr IEEE Transactions on Antennas and Propagation 64 (5), 1963-1968, 2016 | 28 | 2016 |
| MLHOps: Machine learning health operations FK Khattak, V Subasri, A Krishnan, C Pou-Prom, S Akinli-Kocak, ... IEEE Access, 2024 | 26* | 2024 |
| Efficient Evaluation of Bias in Large Language Models through Prompt Tuning T J, D Emerson, D Pandya, L Seyyed-Kalantari, F Khattak NeurIPS Workshop on Socially Responsible Language Modelling Research, 2023 | 21* | 2023 |
| Association between patient race and ethnicity and use of invasive ventilation in the United States FM Abdelmalek, F Angriman, J Moore, K Liu, L Burry, L Seyyed-Kalantari, ... Annals of the American Thoracic Society 21 (2), 287-295, 2024 | 17* | 2024 |
| Adjoint sensitivity analysis of 3D problems with anisotropic materials LS Kalantari, O Ahmed, MH Bakr, NK Nikolova 2014 IEEE MTT-S International Microwave Symposium (IMS2014), 1-3, 2014 | 12 | 2014 |
| Off-label drug use during the COVID-19 pandemic in Africa: topic modelling and sentiment analysis of ivermectin in South Africa and Nigeria as a case study Z Movahedi Nia, NL Bragazzi, A Ahamadi, A Asgary, B Mellado, ... Journal of the Royal Society Interface 20 (206), 20230200, 2023 | 10 | 2023 |
| Medical imaging algorithms exacerbate biases in underdiagnosis L Seyyed-Kalantari, G Liu, M McDermott, I Chen, M Ghassemi | 8 | 2021 |
| Deep learning for computer-aided abnormalities classification in digital mammogram: A data-centric perspective V Nalla, S Pouriyeh, RM Parizi, H Trivedi, QZ Sheng, I Hwang, ... Current Problems in Diagnostic Radiology 53 (3), 346-352, 2024 | 7 | 2024 |
| A TLM-based wideband adjoint variable method for sensitivity analysis of non-dispersive anisotropic structures LS Kalantari, OS Ahmed, MH Bakr, NK Nikolova IEEE Transactions on Antennas and Propagation 65 (10), 5267-5278, 2017 | 7 | 2017 |
| Potential for near-term AI risks to evolve into existential threats in healthcare V Subasri, N Baghbanzadeh, LA Celi, L Seyyed-Kalantari BMJ Health & Care Informatics 32 (1), e101130, 2025 | 6 | 2025 |
| Leveraging deep-learning and unconventional data for real-time surveillance, forecasting, and early warning of respiratory pathogens outbreak ZM Nia, L Seyyed-Kalantari, M Goitom, B Mellado, A Ahmadi, A Asgary, ... Artificial Intelligence in Medicine 161, 103076, 2025 | 6 | 2025 |
Leo Anthony CeliMassachusetts Institute of TechnologyVerified email at mit.edu
