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May 19, 2026Journal of Cosmetic DermatologyOpen Access

Artificial Intelligence‐Augmented Morphometric Reporting for Standardized Facial Aesthetic Treatment Planning: A Multi‐Rater Reliability Study

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Authors

ÖKÖmer KarakoyunKKKadir KayaAKAyşegül Tel Kankılıç

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Overview

Randomized trial evaluates AI impact on inter-rater reliability in facial aesthetic planning, indicating improved consistency.

Key Points

  • To assess the impact of AI-augmented morphometric reports on the consistency of aesthetic treatment plans among dermatologists.
  • Six dermatologists proposed treatment plans for 76 standardized frontal images from the Chicago Face Database.
  • Phase I involved visual assessment, while Phase II utilized AI-augmented reports.
  • Inter-rater reliability was measured using the Intraclass Correlation Coefficient (ICC(2,1)).
  • Inter-rater reliability improved from ICC 0.62 (95% CI: 0.54–0.69) to 0.88 (95% CI: 0.81–0.93) after AI augmentation.
  • The resident group showed the greatest improvement, going from ICC 0.46 to 0.84.
  • Mean absolute deviation from the expert mean decreased from 0.34 to 0.12 scaled units.

Cite This Study

Karakoyun et al. (2026) studied this question.

synapsesocial.com/papers/6a0bfdc7166b51b53d37911chttps://doi.org/10.1111/jocd.70900
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