Disparate censorship & undertesting: A source of label bias in clinical machine learning
As machine learning (ML) models gain traction in clinical applications, understanding the
impact of clinician and societal biases on ML models is increasingly important. While biases …
impact of clinician and societal biases on ML models is increasingly important. While biases …
Targeting repetitive laboratory testing with electronic health records-embedded predictive decision support: A pre-implementation study
Introduction Unnecessary laboratory testing contributes to patient morbidity and healthcare
waste. Despite prior attempts at curbing such overutilization, there remains opportunity for …
waste. Despite prior attempts at curbing such overutilization, there remains opportunity for …