An ExplainableFair Framework for Prediction of Substance Use Disorder Treatment Completion

arXiv:2404.03833v1 Announce Type: new
Abstract: Fairness of machine learning models in healthcare has drawn increasing attention from clinicians, researchers, and even at the highest level of government. On the other hand, the importance of developing and deploying interpretable or explainable models has been demonstrated, and is essential to increasing the trustworthiness and likelihood of adoption of these models. The objective of this study was to develop and implement a framework for addressing both these issues - fairness and explainability. We …

abstract arxiv attention clinicians cs.cy cs.lg fairness framework government healthcare importance machine machine learning machine learning models prediction researchers treatment type