Open-Source 3D Morphing Software for Facial Plastic Surgery and Facial Landmark Detection Research and Open Access Face Data Set Based on Deep Learning (Artificial Intelligence) Generated Synthetic 3D Models

Topsakal, Oguzhan; Glinton, Juan; Akbas, M. Ilhan; Celikoyar, M. Mazhar

doi:10.1089/fpsam.2023.0030

Cited by 8 publications

(2 citation statements)

References 21 publications

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“…The current literature using AI describes various attempts to integrate various functions into preoperative surgical planning, patient education, and assessment of outcomes. [9][10][11][12][13][14][15][16] No study to our knowledge has assessed the feasibility of a patient interactive AI program for answering questions, troubleshooting complications, and providing clinical recommendations during the perioperative period.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence as a Triage Tool during the Perioperative Period: Pilot Study of Accuracy and Accessibility for Clinical Application

Boyd,

Hemal,

Sorenson

et al. 2024

Plastic and Reconstructive Surgery - Global Open

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Background: Given the dialogistic properties of ChatGPT, we hypothesized that this artificial intelligence (AI) function can be used as a self-service tool where clinical questions can be directly answered by AI. Our objective was to assess the content, accuracy, and accessibility of AI-generated content regarding common perioperative questions for reduction mammaplasty. Methods: ChatGPT (OpenAI, February Version, San Francisco, Calif.) was used to query 20 common patient concerns that arise in the perioperative period of a reduction mammaplasty. Searches were performed in duplicate for both a general term and a specific clinical question. Query outputs were analyzed both objectively and subjectively. Descriptive statistics, t tests, and chi-square tests were performed where appropriate with a predetermined level of significance of P less than 0.05. Results: From a total of 40 AI-generated outputs, mean word length was 191.8 words. Readability was at the thirteenth grade level. Regarding content, of all query outputs, 97.5% were on the appropriate topic. Medical advice was deemed to be reasonable in 100% of cases. General queries more frequently reported overarching background information, whereas specific queries more frequently reported prescriptive information (P < 0.0001). AI outputs specifically recommended following surgeon provided postoperative instructions in 82.5% of instances. Conclusions: Currently available AI tools, in their nascent form, can provide recommendations for common perioperative questions and concerns for reduction mammaplasty. With further calibration, AI interfaces may serve as a tool for fielding patient queries in the future; however, patients must always retain the ability to bypass technology and be able to contact their surgeon.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence as a Triage Tool during the Perioperative Period: Pilot Study of Accuracy and Accessibility for Clinical Application

Boyd,

Hemal,

Sorenson

et al. 2024

Plastic and Reconstructive Surgery - Global Open

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“…For the evaluation of reliability, which pertains to the consistency and reproducibility of the test outcomes, the Intraclass Correlation Coefficient (ICC) score is employed [38][39][40][41]. Numerous studies have evaluated the reliability of three-dimensional solutions, including investigations on 3dMDFace [42][43][44][45][46][47][48][49], Canfield Vectra [8], and LifeViz (QuantifiCare) [9]. However, these studies have not encompassed the assessment of area and volume measurements, and they were executed using commercial tools that may not be economically accessible to many healthcare establishments.…”

mentioning

confidence: 99%

Reliability and Agreement of Free Web-Based 3D Software for Computing Facial Area and Volume Measurements

Topsakal,

Sawyer,

Akinci

et al. 2024

BioMedInformatics

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Background: Facial surgeries require meticulous planning and outcome assessments, where facial analysis plays a critical role. This study introduces a new approach by utilizing three-dimensional (3D) imaging techniques, which are known for their ability to measure facial areas and volumes accurately. The purpose of this study is to introduce and evaluate a free web-based software application designed to take area and volume measurements on 3D models of patient faces. Methods: This study employed the online facial analysis software to conduct ten measurements on 3D models of subjects, including five measurements of area and five measurements of volume. These measurements were then compared with those obtained from the established 3D modeling software called Blender (version 3.2) using the Bland–Altman plot. To ensure accuracy, the intra-rater and inter-rater reliabilities of the web-based software were evaluated using the Intraclass Correlation Coefficient (ICC) method. Additionally, statistical assumptions such as normality and homoscedasticity were rigorously verified before analysis. Results: This study found that the web-based facial analysis software showed high agreement with the 3D software Blender within 95% confidence limits. Moreover, the online application demonstrated excellent intra-rater and inter-rater reliability in most analyses, as indicated by the ICC test. Conclusion: The findings suggest that the free online 3D software is reliable for facial analysis, particularly in measuring areas and volumes. This indicates its potential utility in enhancing surgical planning and evaluation in facial surgeries. This study underscores the software’s capability to improve surgical outcomes by integrating precise area and volume measurements into facial surgery planning and assessment processes.

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Future of outcomes research in plastic surgery: Artificial intelligence generated synthetic data and predictive models

Ozmen,

Pinsky,

Schwarz

2024

Journal of Plastic, Reconstructive & Aesthetic Surgery

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Open-Source 3D Morphing Software for Facial Plastic Surgery and Facial Landmark Detection Research and Open Access Face Data Set Based on Deep Learning (Artificial Intelligence) Generated Synthetic 3D Models

Cited by 8 publications

References 21 publications

Artificial Intelligence as a Triage Tool during the Perioperative Period: Pilot Study of Accuracy and Accessibility for Clinical Application

Artificial Intelligence as a Triage Tool during the Perioperative Period: Pilot Study of Accuracy and Accessibility for Clinical Application

Reliability and Agreement of Free Web-Based 3D Software for Computing Facial Area and Volume Measurements

Future of outcomes research in plastic surgery: Artificial intelligence generated synthetic data and predictive models

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