568 citations · 582 across the 15 of their papers we have counts for
4 papers · 1 filter
Algorithms Trained on Normal Chest X-rays Can Predict Health Insurance Types
Chi-Yu Chen, Rawan Abulibdeh, Arash Asgari +8
Artificial intelligence is revealing what medicine never intended to encode. Deep vision models, trained on chest X-rays, can now detect not only disease but also invisible traces…
Benchmarking bias: Expanding clinical AI model card to incorporate bias reporting of social and non-social factors
Carolina A. M. Heming, Mohamed Abdalla, Shahram Mohanna +8
Clinical AI model reporting cards should be expanded to incorporate a broad bias reporting of both social and non-social factors. Non-social factors consider the role of other fact…
Reading Race: AI Recognises Patient's Racial Identity In Medical Images
Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns +20
Background: In medical imaging, prior studies have demonstrated disparate AI performance by race, yet there is no known correlation for race on medical imaging that would be obviou…
CheXclusion: Fairness gaps in deep chest X-ray classifiers
Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew McDermott +2
Machine learning systems have received much attention recently for their ability to achieve expert-level performance on clinical tasks, particularly in medical imaging. Here, we ex…