An Equitable Vision For Wound Assessment: A Comparative Case Study Of AI And Human Wound Tissue Assessment Across Skin Tones

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.

Authors

Publication Details

Journal
Limb Preservation Journal
Published
2025-04-22
DOI
https://doi.org/10.56885/061916taiknw
Primary Topic
Diabetic Foot Ulcer Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Equitable Vision For Wound Assessment: A Comparative Case Study Of AI And Human Wound Tissue Assessment Across Skin Tones

Heba Tallah Mohammed, Samia Rahman, Kaitlyn Ramsay, Ryan S.Q. Geng et al.
Limb Preservation Journal
Diabetic Foot Ulcer Assessment and Management
article

An Equitable Vision For Wound Assessment: A Comparative Case Study Of AI And Human Wound Tissue Assessment Across Skin Tones

Heba Tallah Mohammed, Samia Rahman, Kaitlyn Ramsay, Ryan S.Q. Geng, Robert D. Fraser, Sheila Wang, Samantha Bestavros, Katerina Bavaro
article en

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.

Limb Preservation JournalVol. 6(1)
Openalex Percentile: Top 89%
Diabetic Foot Ulcer Assessment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

An Equitable Vision For Wound Assessment: A Comparative Case Study Of AI And Human Wound Tissue Assessment Across Skin Tones — Heba Tallah Mohammed, Samia Rahman, et al. · Limb Preservation Journal (2025) | TGRS Research Map | TGRS