Addressing fairness in artificial intelligence for medical imaging

In this contribution to Nature, María Agustina Ricci Lara and her co-authors discuss the potential biases in AI systems used in medical imaging and how to address them. 

The article highlights the importance of ensuring that AI systems used in medical imaging are fair and unbiased in their results, as biased results can lead to poor patient outcomes. 

The authors review several approaches that can be taken to address fairness in AI for medical imaging, such as creating diverse training sets, using explainable AI methods, and incorporating human oversight.

They mention that it's important to consider ethical and societal implications when developing AI systems for medical imaging.