AI assistance in aesthetic medicine-A consensus on objective medical standards

Konstantin Frank; Doris Day; Julius Few; Chhabra Chiranjiv; Michael Gold; Sonja Sattler; Martina Kerscher; Leonard Knoedler; Alexandre Filippo; Berthold Rzany; Sebastian Cotofana; Sabrina Fabi; Klaus Fritz; Peter Peng; Rungsima Wanitphakdeedecha; Rainer Pooth; Patrick Huang

doi:10.1111/jocd.16481

AI assistance in aesthetic medicine-A consensus on objective medical standards

J Cosmet Dermatol. 2024 Aug 1. doi: 10.1111/jocd.16481. Online ahead of print.

Authors

Konstantin Frank¹, Doris Day², Julius Few³, Chhabra Chiranjiv⁴, Michael Gold⁵, Sonja Sattler⁶, Martina Kerscher⁷, Leonard Knoedler¹, Alexandre Filippo⁸, Berthold Rzany⁹, Sebastian Cotofana¹⁰, Sabrina Fabi¹¹, Klaus Fritz¹², Peter Peng¹³, Rungsima Wanitphakdeedecha¹⁴, Rainer Pooth¹⁵, Patrick Huang¹⁶

Affiliations

¹ Department of Plastic, Hand and Reconstructive Surgery, University Hospital Regensburg, Regensburg, Germany.
² New York University Langone Health Medical Centers, New York, New York, USA.
³ University of Chicago Pritzker School of Medicine, Chicago, Illinois, USA.
⁴ Skin Alive Clinics, New Delhi, India.
⁵ Gold Skin Care Center, Tennessee Clinical Research Center, Nashville, Tennessee, USA.
⁶ Rosenpark Klinik, Darmstadt, Germany.
⁷ Department of Chemistry, Division of Cosmetic Sciences, University of Hamburg, Hamburg, Germany.
⁸ Instituto de Dermatologia Prof. Rubem David Azulay, Rio de Janeiro, Brazil.
⁹ Medizin am Hauptbahnhof, Wien, Austria and Hautarzt Friedenau, Berlin, Germany.
¹⁰ Department of Dermatology, Erasmus Medical Centre, Rotterdam, The Netherlands.
¹¹ University of California San Diego, San Diego, California, USA.
¹² Dermatology and Laser Center, Landau in der Pfalz, Germany.
¹³ P-Skin Professional Clinic, Taipei, Taiwan.
¹⁴ Department of Dermatology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand.
¹⁵ Clinical Research and Development, ICA Aesthetic Navigation GmbH, Frankfurt, Germany.
¹⁶ Huang PH Dermatology and Aesthetics, Taipei, Taiwan.

PMID: 39091136
DOI: 10.1111/jocd.16481

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.

Keywords: aesthetic medicine; artificial intelligence; consensus meeting; medical technology; objective standards.