Validity of facial skin analysis pore detection: A comparative analysis

Reliable, objective measures to assess facial characteristics would aid in the assessment of many dermatological treatments. Previous work utilized an iOS application-based artificial intelligence (AI) tool compared to the "gold standard" computer-based and a physician assessment on five skin metrics (British Journal of Dermatology, 2013, 169, 474). The AI tool had superior agreement for all skin metrics except pores and subsequently underwent an algorithm update for its pore detection system.

This comparative analysis assessed the performance of the updated AI tool's pore scores across all Fitzpatrick skin phototypes to determine whether the AI tool more accurately represents a dermatologist's assessment of pores.

Frontal facing photographs in uniform lighting conditions were taken of each participant. Percentile scores were generated by each of the four self-learning models of the updated AI tool. The pore percentile scores generated by the original and updated AI tool were used to rate "worse" pores among participant pairs. These ratings were compared to pore assessments performed by a "gold-standard" device and a board-certified dermatologist.

Compared to the original pore detection tool and the computer-based program, models A and D had the highest concordance with the physician's pore assessments for Fitzpatrick skin phototypes III-IV and V-VI, respectively.

The AI tool's pores detection update was successful in its ability to accurately detect pores on all Fitzpatrick skin types, improving on the performance of the AI prior to the update. Responsibly developed AI tools that can accurately and reliably detect skin metrics across diverse Fitzpatrick skin types can facilitate dermatologic evaluation, individualize treatment, and determine treatment response.