2024
DOI: 10.1101/2024.03.16.24304403
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A Survey on Optimization and Machine Learning-Based Fair Decision Making in Healthcare

Zequn Chen,
Wesley J. Marrero

Abstract: Background. Unintended biases introduced by optimization and machine learning (ML) models are of great interest to medical professionals. Bias in healthcare decisions can cause patients from vulnerable populations (e.g., racially minoritized, low-income) to have lower access to resources, exacerbating societal unfairness. Purpose. This review aims to identify, describe, and categorize literature regarding bias types, fairness metrics, and bias mitigation methods in healthcare decision making. Data Sources. Goo… Show more

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