An Equitable Vision For Wound Assessment: A Comparative Case Study Of AI And Human Wound Tissue Assessment Across Skin Tones
DOI: 10.56885/061916taiknw
Heba Tallah Mohammed PhD MD, Sheila Wang PhD, Samia Rahman BSc, Ryan SQ Geng MSc, Kaitlyn Ramsay PhD, Samantha Bestavros BSc, Katerina Bavaro HBSc,, Robert DJ Fraser MN RN WOCC© NSWOCC
Abstract: Accurate wound assessment is crucial for effective wound management, but visual assessment can be inconsistent due to various clinician (e.g., knowledge, skill) or patient (e.g., skin tone) factors. This study compares clinicians’ subjective assessments of wound tissues with those made by an artificial intelligence (AI) model (SmartTissueTM) across different skin tones. The study highlights the subjective nature of manual wound assessments and the potential value of AI driven documentation in clinical practice. The integration of AI technology could offer clinicians real-time data aiding in standardizing measurements across diverse populations to reduce racial disparities in wound care. By providing consistent, standardized measurements across diverse patient populations, AI can support clinical judgment in evaluating wound healing, monitoring treatment efficacy and revising care planning.