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Detecting algorithmic bias in medical AI-models
Feb. 29, 2024, 5:43 a.m. | Jeffrey Smith, Andre Holder, Rishikesan Kamaleswaran, Yao Xie
cs.LG updates on arXiv.org arxiv.org
Abstract: With the growing prevalence of machine learning and artificial intelligence-based medical decision support systems, it is equally important to ensure that these systems provide patient outcomes in a fair and equitable fashion. This paper presents an innovative framework for detecting areas of algorithmic bias in medical-AI decision support systems. Our approach efficiently identifies potential biases in medical-AI models, specifically in the context of sepsis prediction, by employing the Classification and Regression Trees (CART) algorithm. We …
abstract algorithmic bias artificial artificial intelligence arxiv bias cs.cy cs.lg decision decision support fair fashion framework intelligence machine machine learning medical medical ai paper patient stat.ap stat.ml support systems type
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