Careful of embedded AI

AIMedical DeviceHealth Equity
Written By Khalil Thomas

As #AI solutions are further embedded across the #healthcare continuum, studies like the one below continue to highlight the risk posed by these solutions to the patients we hope to help if certain factors are not considered by design and #validation teams. Bottom line: #machinelearning tools can't fix your broken processes for you. To the contrary, they are more likely to systemize your past poor performance.

For my #quality professionals, how are you ensuring your design teams are considering these risks? How can Verification and Validation plans/teams be better structured to control for these kinds of failures? How are you staffing your #audit teams to identify deficiencies?

https://www.nature.com/articles/d41586-019-03228-6

Khalil Thomas

Khalil Thomas is a Health Equity expert and President of TRCG, a boutique Digital Health consulting group that leverages regulatory compliance expertise to bring solutions to market, manage algorithm bias, and improve quality for an expanded patient demographic. He specializes in topics at the intersection of AI, Health Tech, and Health Equity; highlighting pathways for innovation enabled equity.

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Health Equity, the Quality Professional’s Dilemma