4 papers
Reliable fairness auditing with semi-supervised inference
Jianhui Gao, Jessica Gronsbell
Machine learning (ML) models often exhibit bias that can exacerbate inequities in biomedical applications. Fairness auditing, the process of evaluating a model's performance across…
Another look at statistical inference with machine learning-imputed data
Jessica Gronsbell, Jianhui Gao, Zachary R. McCaw +2
From structural biology to epidemiology, predictions from machine learning (ML) models increasingly complement costly gold-standard data, enabling faster, more affordable, and scal…
Fairmetrics: An R package for group fairness evaluation
Benjamin Smith, Jianhui Gao, Jessica Gronsbell
Fairness is a growing area of machine learning (ML) that focuses on ensuring models do not produce systematically biased outcomes for specific groups, particularly those defined by…
What is Fair? Defining Fairness in Machine Learning for Health
Jianhui Gao, Benson Chou, Zachary R. McCaw +4
Ensuring that machine learning (ML) models are safe, effective, and equitable across all patients is critical for clinical decision-making and for preventing the amplification of e…