The Racial Representation of Cosmetic Surgery Patients and Physicians on Social Media

Ullrich, Peter J; Garg, Stuti; Reddy, Narain; Hassan, Abbas M.; Joshi, Chitang J.; Perez, Laura; Tassinari, Stefano; Galiano, Robert D.

doi:10.1093/asj/sjac099

Cited by 7 publications

(7 citation statements)

References 20 publications

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“…A total of 138 publications were identified 3–140 Figure 1. demonstrates the number of publications appearing annually in the 6 journals from January 2018 to September 2023.…”

Section: Resultsmentioning

confidence: 99%

Diversity, Equity, and Inclusion in Plastic Surgery

Swanson

2024

Ann Plast Surg

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Background The number of publications on the subject of diversity, equity, and inclusion has surged in the last 5 years. However, a systematic review of this topic has not been published. Method Six top plastic surgery journals were queried from 2018 to 2023 using the search term “diversity.” Methods, conclusions, and recommendations were tabulated. Results A total of 138 publications were identified; 68 studies presented data suitable for analysis. All studies were retrospective. Currently, over 40% of plastic surgery residency applicants are women. The proportion of women in integrated plastic surgery residents is now 43%. In 2021 and 2022, the percentage of female first-year residents exceeded men. The percentage of female presenters at meetings (34%) is double the number in the workforce (17%). Twenty-five percent of academic faculty positions and 22% of program director positions are now held by women. Underrepresented minorities account for fewer than 10% of applicants to integrated plastic surgery residencies. Discussion The proportion of Black and Hispanic applicants to integrated plastic surgery residencies (6% and 8%, respectively) mirrors the proportion of Black and Hispanic medical students (7% and 6%, respectively). Numerous recommendations have been made to increase the proportion of underrepresented minorities in plastic surgery programs. Conclusions The representation of women in plastic surgery has increased dramatically. A lack of Hispanics and Blacks reflects a small pool of applicants, as opposed to a “leaky pipeline.”

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“…A total of 138 publications were identified 3–140 Figure 1. demonstrates the number of publications appearing annually in the 6 journals from January 2018 to September 2023.…”

Section: Resultsmentioning

confidence: 99%

Diversity, Equity, and Inclusion in Plastic Surgery

Swanson

2024

Ann Plast Surg

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“…Currently, lack of representation of black patients and providers in blepharoplasty or rhinoplasty procedures, can impact accuracy of algorithms. [38] Measurements acquired from AI provide only numerical expressions of opinions and subjective evaluations of publishing healthcare providers. AI's definition is therefore subject to cultural and personal influences.…”

Section: Predictive Analyticsmentioning

confidence: 99%

Exploring the Practical Applications of Artificial Intelligence, Deep Learning, and Machine Learning in Maxillofacial Surgery: A Comprehensive Analysis of Published Works

Czako,

Sufliarsky,

Simko

et al. 2024

Preprint

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Artificial intelligence (AI), deep learning (DL) or machine learning (ML) is the ability of computer systems, machines and enginery to work devise procedures like humans. These technologies provide opportunities and possibilities to advance diagnostics and in planning also in the field of human medicine and dentistry. The purpose of this literature review was to ascertain the applicability and significance of AI, as well as to highlight its uses in maxillofacial surgery. The primary inclusion criterion for this publication was an original paper written in English focusing on the use of AI, DL or ML in maxillofacial surgery. The sources of information were PubMed, Scopus and Web of Science, and the queries were made on 31st of December 2023. The search strings used were “artificial intelligence maxillofacial surgery”, “machine learning maxillofacial surgery” and “deep learning maxillofacial surgery”. Following the removal of duplicates, all remaining publications that were returned by the searches and were screened by three independent operators to minimize the risk of bias. The analysis of publications from 1992 to 2023 identified certain records, of which 324 were finally selected. These were calculated according to the year of publication with a continuous increase (excluding 2012 and 2013) of R2 = 0.9295. Generally, in orthognathic dentistry and maxillofacial surgery, artificial intelligence and machine learning have gained popularity over the past few decades. When we included the keywords "planning in maxillofacial surgery" and "planning in orthognathic surgery", the set of published papers significantly increased to the number of 7535 publications. The first publication appeared in 1965, with an increasing trend (excluding 2014-2018), with an R2 value of 0.8642. These tools have been found useful for diagnosis, treatment planning in head and neck surgical oncology, cosmetic and aesthetic surgery, and in oral pathology. In orthognathic surgery, they have been utilised for diagnosis, treatment planning, assessment of treatment needs, cephalometric analyses, and orthognathic surgeries, among other applications. The review confirms that the current use of artificial intelligence and machine learning in maxillofacial surgery is focused mainly on the evaluation of digital diagnostic methods especially radiology, treatment plans and postoperative results. However, as these technologies are integrated in maxillofacial surgery and robotic surgery in head and neck region, it is expected that in the future they will be gradually utilized to plan and comprehensively evaluate the success of maxillofacial surgeries.

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“…However, collecting datasets from different centers containing different genders, ages, and nationalities will increase the generalizability of the AI model. Black patients and providers are underrepresented in rhinoplasty and blepharoplasty [30]. It is essential to discuss the validity of assessing attractiveness based on data obtained from a dating platform.…”

Section: Ethical Issuesmentioning

confidence: 99%

Artificial intelligence applications and ethical challenges in oral and maxillo-facial cosmetic surgery: a narrative review

Rokhshad

Keyhan

Yousefi³

2023

Maxillofac Plast Reconstr Surg

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Artificial intelligence (AI) refers to using technologies to simulate human cognition to solve a specific problem. The rapid development of AI in the health sector has been attributed to the improvement of computing speed, exponential increase in data production, and routine data collection. In this paper, we review the current applications of AI for oral and maxillofacial (OMF) cosmetic surgery to provide surgeons with the fundamental technical elements needed to understand its potential. AI plays an increasingly important role in OMF cosmetic surgery in various settings, and its usage may raise ethical issues. In addition to machine learning algorithms (a subtype of AI), convolutional neural networks (a subtype of deep learning) are widely used in OMF cosmetic surgeries. Depending on their complexity, these networks can extract and process the elementary characteristics of an image. They are, therefore, commonly used in the diagnostic process for medical images and facial photos. AI algorithms have been used to assist surgeons with diagnosis, therapeutic decisions, preoperative planning, and outcome prediction and evaluation. AI algorithms complement human skills while minimizing shortcomings through their capabilities to learn, classify, predict, and detect. This algorithm should, however, be rigorously evaluated clinically, and a systematic ethical reflection should be conducted regarding data protection, diversity, and transparency. It is possible to revolutionize the practice of functional and aesthetic surgeries with 3D simulation models and AI models. Planning, decision-making, and evaluation during and after surgery can be improved with simulation systems. A surgical AI model can also perform time-consuming or challenging tasks for surgeons.

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The Racial Representation of Cosmetic Surgery Patients and Physicians on Social Media

Cited by 7 publications

References 20 publications

Diversity, Equity, and Inclusion in Plastic Surgery

Diversity, Equity, and Inclusion in Plastic Surgery

Exploring the Practical Applications of Artificial Intelligence, Deep Learning, and Machine Learning in Maxillofacial Surgery: A Comprehensive Analysis of Published Works

Artificial intelligence applications and ethical challenges in oral and maxillo-facial cosmetic surgery: a narrative review

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