Laleh Seyyed-Kalantari
Laleh Seyyed-Kalantari
Assistant Professor, York University
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Cited by
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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
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
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
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
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
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
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
Evaluating knowledge transfer in the neural network for medical images
S Akbarian, L Seyyed-Kalantari, F Khalvati, E Dolatabadi
IEEE Access, 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, 2023
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
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
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
Medical imaging algorithms exacerbate biases in underdiagnosis
L Seyyed-Kalantari, G Liu, M McDermott, I Chen, M Ghassemi
Detection, identification and tracking of flying objects in three dimensions using multistatic radars
SK Laleh, M Shahram, T Saeed
Int'l J. of Communications, Network and System Sciences 2009, 2009
Soft-prompt Tuning for Large Language Models to Evaluate Bias
JJ Tian, D Emerson, SZ Miyandoab, D Pandya, L Seyyed-Kalantari, ...
arXiv preprint arXiv:2306.04735, 2023
The Challenge Dataset–simple evaluation for safe, transparent healthcare AI deployment
JK Sanayei, M Abdalla, M Ahluwalia, L Seyyed-Kalantari, S Minotti, ...
medRxiv, 2022.12. 15.22280619, 2022
Reply to:‘Potential sources of dataset bias complicate investigation of underdiagnosis by machine learning algorithms’ and ‘Confounding factors need to be accounted for in …
L Seyyed-Kalantari, H Zhang, MBA McDermott, IY Chen, M Ghassemi
Nature Medicine 28 (6), 1161-1162, 2022
Optical cloak design exploiting efficient anisotropic adjoint sensitivity analysis
LS Kalantari, MH Bakr
Applied Computational Electromagnetics Society Journal 32 (5), 449, 2017
Cloaking exploiting anisotropic adjoint sensitivity analysis
LS Kalantari, MH Bakr
2015 IEEE International Symposium on Antennas and Propagation & USNC/URSI …, 2015
Design and simulation of a Multistatic radar system and optimizing the radar sites positions using multiobjective genetic algorithms
S Mohanna, LS Kalantari, S Tavakoli
J. Passive Defence Sci. Tech 4, 241-247, 2011
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