Author:
Yoelin Steve,Green Jeremy B,Dhawan Sunil S,Hasan Fauad,Mahbod Brom,Khan Bashir,Dhawan Akash S
Abstract
Abstract
Background
Artificial intelligence (AI) platforms are increasingly being utilized in various healthcare applications. There are few platforms that provide quantifiable assessments of dermatologic or aesthetic conditions by employing industry established scales.
Objectives
The authors sought to report the results of a pilot study that evaluated the utilization and functionality of an AI engine to measure and monitor rhytids (fine lines). For this study, glabellar frown lines were employed as the clinical model.
Methods
Seventy-one patients were enrolled and monitored remotely employing current high-quality mobile phone cameras over a 14-day period. The patients were prompted to take photographs employing this platform at preset intervals, and these photographs were then rated by the AI platform and qualified raters experienced in the field of facial aesthetics.
Results
The AI platform had concordance with 2 qualified raters of 46% to 68%, and the inter-rater concordance between 2 rates ranged from 44% to 66%. The intra-rater concordance for the raters was between 57% and 84%, whereas the AI platform had a 100% concordance with itself. The participant and investigator satisfaction ratings of the platform were high on multiple dimensions of the platform.
Conclusions
This AI platform evaluated photos on a comparable level of accuracy as the qualified raters, and it evaluated more consistently than the qualified raters. This platform may have high utility in clinical research and development, including the management of clinical trials, and efficient management of patient care at the clinical practices.
Publisher
Oxford University Press (OUP)
Cited by
4 articles.
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