Investigating for bias in healthcare algorithms: a sex-stratified analysis of supervised machine learning models in liver disease prediction.

Journal: BMJ health & care informatics
Published Date:

Abstract

OBJECTIVES: The Indian Liver Patient Dataset (ILPD) is used extensively to create algorithms that predict liver disease. Given the existing research describing demographic inequities in liver disease diagnosis and management, these algorithms require scrutiny for potential biases. We address this overlooked issue by investigating ILPD models for sex bias.

Authors

  • Isabel Straw
    Department of Public Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
  • Honghan Wu
    University College London, London, United Kingdom.