relation: http://publicatio.bibl.u-szeged.hu/34531/
title: The Potential of AI-Powered Face Enhancement Technologies in Face-Driven Orthodontic Treatment Planning
creator:  Tomášik Juraj
creator:  Zsoldos Márton
creator:  Majdáková Kristína
creator:  Fleischmann Alexander
creator:  Oravcová Ľubica
creator:  Sónak Ballová Dominika
creator:  Thurzo Andrej
subject: 03.02. Klinikai orvostan
description: Improving one’s appearance is one of the main reasons to undergo an orthodontic therapy. While occlusion is important, not just for long-term stability, aesthetics is often considered a key factor in patient’s satisfaction. Following recent advances in artificial intelligence (AI), this study set out to investigate whether AI can help guide orthodontists in diagnosis and treatment planning. In this study, 25 male and 25 female faces were generated and consequently enhanced using FaceApp (ver. 11.10, FaceApp Technology Limited, Limassol, Cyprus), one of the many pictures transforming applications on the market. Both original and FaceApp-modified pictures were then assessed by 441 respondents regarding their attractiveness, and the pictures were further compared using a software for picture analyses. Statistical analysis was performed using Chi-square goodness of fit test R Studio Studio (ver. 4.1.1, R Core Team, Vienna, Austria) software and the level of statistical significance was set to 0.05. The interrater reliability was tested using Fleiss’ Kappa for m Raters. The results showed that in 49 out of 50 cases, the FaceApp-enhanced pictures were considered to be more attractive. Selected pictures were further analyzed using the graphical software GIMP. The most prominent changes were observed in lip fullness, eye size, and lower face height. The results suggest that AI-powered face enhancement could be a part of the diagnosis and treatment planning stages in orthodontics. These enhanced pictures could steer clinicians towards soft-tissue-oriented and personalized treatment planning, respecting patients’ wishes for improved face appearance.
date: 2024
type: Folyóiratcikk
type: PeerReviewed
format: text
identifier: http://publicatio.bibl.u-szeged.hu/34531/1/applsci-14-07837-with-cover.pdf
identifier:     Tomášik Juraj;  Zsoldos Márton;  Majdáková Kristína;  Fleischmann Alexander;  Oravcová Ľubica;  Sónak Ballová Dominika;  Thurzo Andrej: The Potential of AI-Powered Face Enhancement Technologies in Face-Driven Orthodontic Treatment Planning.   APPLIED SCIENCES-BASEL, 14 (17).   ISSN 2076-3417 (2024)     
identifier: doi:10.3390/app14177837
relation: https://doi.org/10.3390/app14177837
relation: 35203163
language: eng