Not all biases are bad: equitable and inequitable biases in machine learning and radiology

Not all biases are bad: equitable and inequitable biases in machine learning and radiology

Abstract The application of machine learning (ML) technologies in medicine generally but also in radiology more specifically is hoped to improve clinical processes and the provision of healthcare. A central motivation in this regard is to advance patient treatment by reducing human error and increas...

Full description

Bibliographic Details
Main Authors: Mirjam Pot, Nathalie Kieusseyan, Barbara Prainsack
Format: Article
Language:English
Published: SpringerOpen 2021-02-01
Series:Insights into Imaging
Subjects:
Radiology
Machine learning
Equity
Bias
Ethics
Online Access:https://doi.org/10.1186/s13244-020-00955-7

Internet

https://doi.org/10.1186/s13244-020-00955-7

Similar Items