Evaluating gender bias in ML-based clinical risk prediction models: A study on multiple use cases at different hospitals

Author:

Cabanillas Silva Patricia,Sun HongORCID,Rodriguez-Brazzarola PabloORCID,Rezk Mohamed,Zhang Xianchao,Fliegenschmidt Janis,Hulde Nikolai,von Dossow Vera,Meesseman LaurentORCID,Depraetere Kristof,Szymanowsky Ralph,Stieg Jörg,Dahlweid Fried-Michael

Publisher

Elsevier BV

Reference32 articles.

1. A. Agarwal, A. Beygelzimer, M. Dudík, J. Langford, H. Wallach, A Reductions Approach to Fair Classification, 2018.

2. Sex and gender differences and biases in artificial intelligence for biomedicine and healthcare;Cirillo;Npj Digit. Med.,2020

3. Invisible Women: Exposing Data Bias in a World Designed for Men;Criado-Perez,2019

4. Machine intelligence in healthcare—perspectives on trustworthiness, explainability, usability, and transparency;Cutillo;Npj Digit. Med.,2020

5. 12 Plagues of AI in Healthcare: a practical guide to current issues with using machine learning in a medical context;Doyen;Front. Digit. Health,2022

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