Addressing racial disparities in surgical care with machine learning

There is ample evidence to demonstrate that discrimination against several population subgroups interferes with their ability to receive optimal surgical care. This bias can take many forms, including limited access to medical services, poor quality of care, and inadequate insurance coverage. While such inequalities will require numerous cultural, ethical, and sociological solutions, artificial intelligence-based algorithms may help address the problem by detecting bias in the data sets currently being used to make medical decisions. However, such AI-based solutions are only in early development. The purpose of this commentary is to serve as a call to action to encourage investigators and funding agencies to invest in the development of these digital tools.

Automated summary

Discrimination against population subgroups hinders their ability to receive optimal surgical care. Artificial intelligence algorithms can potentially address this issue by detecting bias in current medical decision-making datasets, but further investment and development are needed.