AI assistance in aesthetic medicine–A consensus on objective medical standards
Issued Date
2024-01-01
Resource Type
ISSN
14732130
eISSN
14732165
Scopus ID
2-s2.0-85200243271
Journal Title
Journal of Cosmetic Dermatology
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of Cosmetic Dermatology (2024)
Suggested Citation
Frank K., Day D., Few J., Chiranjiv C., Gold M., Sattler S., Kerscher M., Knoedler L., Filippo A., Rzany B., Cotofana S., Fabi S., Fritz K., Peng P., Wanitphakdeedecha R., Pooth R., Huang P. AI assistance in aesthetic medicine–A consensus on objective medical standards. Journal of Cosmetic Dermatology (2024). doi:10.1111/jocd.16481 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/100424
Title
AI assistance in aesthetic medicine–A consensus on objective medical standards
Author's Affiliation
Siriraj Hospital
Erasmus MC
NYU Langone Health
University of California, San Diego
Universität Hamburg
Gold Skin Care Center
Klinikum der Universität Regensburg und Medizinische Fakultät
Pritzker School of Medicine
Wien
Huang PH Dermatology and Aesthetics
Dermatology and Laser Consultation Center
P-Skin Professional Clinic
ICA Aesthetic Navigation GmbH
Skin Alive Clinics
Instituto de Dermatologia Professor Rubem David Azulay
Rosenparkklinik
Erasmus MC
NYU Langone Health
University of California, San Diego
Universität Hamburg
Gold Skin Care Center
Klinikum der Universität Regensburg und Medizinische Fakultät
Pritzker School of Medicine
Wien
Huang PH Dermatology and Aesthetics
Dermatology and Laser Consultation Center
P-Skin Professional Clinic
ICA Aesthetic Navigation GmbH
Skin Alive Clinics
Instituto de Dermatologia Professor Rubem David Azulay
Rosenparkklinik
Corresponding Author(s)
Other Contributor(s)
Abstract
Background: Aesthetic medicine has traditionally relied on clinical scales for the objective assessment of baseline appearance and treatment outcomes. However, the scales focus on limited aesthetic areas mostly and subjective interpretation inherent in these scales can lead to variability, which undermines standardization efforts. Objective: The consensus meeting aimed to establish guidelines for AI application in aesthetic medicine. Materials and Methods: In February 2024, the AI Consensus Group, comprising international experts in various specialties, convened to deliberate on AI in aesthetic medicine. The methodology included a pre-consensus survey and an iterative consensus process during the meeting. Results: AI's implementation in Aesthetic Medicine has achieved full consensus for enhancing patient assessment and consultation, ensuring standardized care. AI's role in preventing overcorrection is recognized, alongside the need for validated objective facial assessments. Emphasis is placed on comprehensive facial aesthetic evaluations using indices such as the Facial Aesthetic Index (FAI), Facial Youth Index (FYI), and Skin Quality Index (SQI). These evaluations are to be gender-specific and exclude makeup-covered skin at baseline. Age and gender, as well as patients' ancestral roots, are to be considered integral to the AI assessment process, underlining the move towards personalized, precise treatments. Conclusion: The consensus meeting established that AI will significantly improve aesthetic medicine by standardizing patient assessments and consultations, with a strong endorsement for preventing overcorrection and advocating for validated, objective facial assessments. Utilizing indices such as the FAI, FYI, and SQI allows for gender-specific, age adjusted evaluations and insists on a makeup-free baseline for accuracy.