Faculty profile
Laleh Seyyed-Kalantari
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Research
Latest papers
Rethinking fairness in AI to improve current practice in oncology.
Trends in cancer · 2026 · senior author
Potential for near-term AI risks to evolve into existential threats in healthcare.
BMJ health & care informatics · 2025 · senior author
Subgroup evaluation to understand performance gaps in deep learning-based classification of regions of interest on mammography.
PLOS digital health · 2025
Latest funding
- $12,500
Mitigating the unfairness of AI-based medical image diagnostic tools
NSERC · 2023 · Principal investigator
- $62,000
Mitigating the unfairness of AI-based medical image diagnostic tools
NSERC · 2023 · Principal investigator
- $121,762
Training an AI to detect medical bias and unmet health needs through critical race and disability theory and community-generated data
SSHRC · 2022 · Co-investigator
13 publications.
Rethinking fairness in AI to improve current practice in oncology.
Konate S, Gallifant J, Senteio C, Celi LA, Seyyed-Kalantari L
Potential for near-term AI risks to evolve into existential threats in healthcare.
Subasri V, Baghbanzadeh N, Celi LA, Seyyed-Kalantari L
Subgroup evaluation to understand performance gaps in deep learning-based classification of regions of interest on mammography.
Woo M, Zhang L, Brown-Mulry B, Hwang I, Gichoya JW, Gastounioti A, Banerjee I, Seyyed-Kalantari L, Trivedi H
Interpretability of AI race detection model in medical imaging with saliency methods.
Konate S, Lebrat L, Cruz RS, Wawira Gichoya J, Price B, Seyyed-Kalantari L, Fookes C, Bradley A, Salvado O
Deep learning for computer-aided abnormalities classification in digital mammogram: A data-centric perspective.
Nalla V, Pouriyeh S, Parizi RM, Trivedi H, Sheng QZ, Hwang I, Seyyed-Kalantari L, Woo M
Association between Patient Race and Ethnicity and Use of Invasive Ventilation in the United States.
Abdelmalek FM, Angriman F, Moore J, Liu K, Burry L, Seyyed-Kalantari L, Mehta S, Gichoya J, Celi LA, Tomlinson G, Fralick M, Yarnell CJ
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
"Shortcuts" Causing Bias in Radiology Artificial Intelligence: Causes, Evaluation, and Mitigation.
Banerjee I, Bhattacharjee K, Burns JL, Trivedi H, Purkayastha S, Seyyed-Kalantari L, Patel BN, Shiradkar R, Gichoya J
Impact of multi-source data augmentation on performance of convolutional neural networks for abnormality classification in mammography.
Hwang I, Trivedi H, Brown-Mulry B, Zhang L, Nalla V, Gastounioti A, Gichoya J, Seyyed-Kalantari L, Banerjee I, Woo M
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'.
Seyyed-Kalantari L, Zhang H, McDermott MBA, Chen IY, Ghassemi M
Mitigating the unfairness of AI-based medical image diagnostic tools
Principal investigators: Seyyed-Kalantari, Laleh
Mitigating the unfairness of AI-based medical image diagnostic tools
Principal investigators: Seyyed-Kalantari, Laleh
Keywords: artificial intelligence; medical imaging; fairness; bias; mitigating unfairness; decision making; medical image; trustworthy ai; ai diagnostic tools; ai and ethic
Training an AI to detect medical bias and unmet health needs through critical race and disability theory and community-generated data
Principal investigators: Gorman, Rachel
Keywords: AI bias; medical bias; natural language processing; medically unexplained illness; medical sexism, racism & ableism; social determinants of health; cellular and biochemical bases of chronic illness; microaggressions in healthcare interactions; electronic medical records; community-based health narratives
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
- Lisa Burry and Sangeeta Mehta: 37 shared papers
- George Tomlinson and Sangeeta Mehta: 6 shared papers
- George Tomlinson and Michael Fralick: 6 shared papers
- Lisa Burry and George Tomlinson: 5 shared papers
- Marzyeh Ghassemi and Laleh Seyyed-Kalantari: 2 shared papers
- Lisa Burry and Michael Fralick: 1 shared paper
- Lisa Burry and Laleh Seyyed-Kalantari: 1 shared paper
- George Tomlinson and Laleh Seyyed-Kalantari: 1 shared paper
- Marzyeh Ghassemi and Michael Fralick: 1 shared paper
- Sangeeta Mehta and Michael Fralick: 1 shared paper
- Sangeeta Mehta and Laleh Seyyed-Kalantari: 1 shared paper
- Michael Fralick and Laleh Seyyed-Kalantari: 1 shared paper
- Electrical Engineering and Computer Science
- General Internal Medicine
- Biostatistics Division
- Pharmacy
- Other
Co-authors at York University, colored by department. Thicker lines mean more shared papers; select anyone to open their profile and their own map.
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