A Breakthrough in Trust for AI Diagnostics
How a transparent AI framework helped reduce physician overrides from 87% to 1.7%
Trust in AI doesn’t come from algorithms alone; it comes from transparency and confidence in the recommendations those algorithms deliver.
In a peer-reviewed study led by Dr. Yunguo Yu, VP of AI Innovations & Prototyping at Zyter|TruCare, and researchers from the Mayo Clinic, introducing a framework that incorporated AI transparency and confidence levels led to a remarkable drop in physician overrides of AI-generated diagnoses, from 87% to as low as 1.7%.
To make these findings more accessible, we’ve developed a concise infographic highlighting the key insights and outcomes from this pivotal study. It’s designed to help healthcare leaders and care teams quickly understand how trust-calibrated AI can:
- Reduce diagnostic delays
- Strengthen clinical decision-making
- Ease operational burdens
- Support quality, access, and financial balance across risk-bearing models
Download the Infographic
Complete the form below to access the infographic and learn what it takes to build AI that care teams actually trust.
