Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis
Consejo Nacional de Investigaciones Científicas y Técnicas · Universidad Nacional del Litoral · +1 more institution
Abstract
Artificial intelligence (AI) systems for computer-aided diagnosis and image-based screening are being adopted worldwide by medical institutions. In such a context, generating fair and unbiased classifiers becomes of paramount importance. The research community of medical image computing is making great efforts in developing more accurate algorithms to assist medical doctors in the difficult task of disease diagnosis. However, little attention is paid to the way databases are collected and how this may influence the performance of AI systems. Our study sheds light on the importance of gender balance in medical imaging datasets used to train AI systems for computer-assisted diagnosis. We provide empirical…
Citation impact
- FWCI
- 19.32
- Percentile
- 100%
- References
- 38
Authors
5- AJAgostina J. LarrazabalCorresponding
Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional del Litoral
- NNNicolás Nieto
Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional del Litoral
- VPVictoria Peterson
Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional del Litoral, Universidad Nacional de Entre Ríos
- DHDiego H. Milone
Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional del Litoral
- EFEnzo Ferrante
Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Nacional del Litoral
Topics & keywords
- Computer science
- Artificial intelligence
- Machine learning
- Robustness (evolution)
- Medical imaging
- Context (archaeology)
- Balance (ability)
- Data science
- Gender equality