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VERSION:2.0
PRODID:-//AfroTech Conference//Schedule//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
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UID:e9391d86-27fa-4a75-9eca-a8cafb0f601f@afrotechconference.com
DTSTAMP:20260904T215958Z
DTSTART:20261104T172000Z
DTEND:20261104T182000Z
SUMMARY:Building Fairness Into the Data Supply Chain
DESCRIPTION:Bias in healthcare AI begins before training\, embedded in decisions about missing data\, labels\, and success metrics. Waverly Rose Brim demonstrates how a clinical prediction model with strong global performance can still fail Black patients and the underinsured\, then walks through a fairness-aware correction workflow. Attendees leave with a practical framework for equity-first dataset design and go/no-go deployment standards.\n\nSession ID: e9391d86-27fa-4a75-9eca-a8cafb0f601f\n\nhttps://afrotechconference.com/schedule#session-e9391d86-27fa-4a75-9eca-a8cafb0f601f
LOCATION:HealthStack General Session (Marriott)
URL:https://afrotechconference.com/schedule#session-e9391d86-27fa-4a75-9eca-a8cafb0f601f
X-WR-TIMEZONE:America/Chicago
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