aceBias in medical AI: Implications for clinical decision-making
Biases in medical artificial intelligence (AI) arise and compound throughout the AI lifecycle. These biases can have significant clinical consequences, especially in applications that involve clinical decision-making. Left unaddressed, biased medical AI can lead to substandard clinical decisions and the perpetuation and exacerbation of longstanding healthcare disparities. We discuss potential biases that can arise at different stages in the AI development pipeline and how they can affect AI algorithms and clinic…
Biased medical AI can lead to substandard clinical decisions and perpetuate healthcare disparities, with performance deteriorating differentially across patient subgroups when deployed outside training cohorts.
Evidence
- Peer-reviewedPLOS Digital Health2024-11-07
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Truvace Impact Record TRV-2026-0278, v1: “Bias in medical AI: Implications for clinical decision-making.” Truvace, 2026-07-19. /record/TRV-2026-0278 (accessed at citation time). sha256 27ba521612da2a4b…
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