AI & Quality

Medical DeviceAI
Written By Khalil Thomas

Last week I had the opportunity to host a session on one of my favorite topics, #AI applications for #QualitySystems at the 11th Medical Device Safety Monitoring Reporting And Surveillance meeting in San Diego. In the session I highlighted some common AI technologies and their immense potential for time savings and error reduction, along with some of their hidden dangers for different quality system elements, some common pitfalls, and (of course, for the auditor in me 😉) some #audit survival tips for these solutions.

Of most interest to the group was the potential of #machinelearning for #complaintshandling and reporting activities. This particularly ripe application is exciting for me having been involved with (and auditing) one such implementation. What interesting AI applications have you seen for #Quality Systems? What's something you wish someone told you before beginning your AI journey?

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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