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This paper explores the evolving efforts to quantify beauty, tracing its path from mythological ideals to modern algorithms. Inspired by the legendary face of Helen of Troy-the mortal echo of Aphrodite-whose beauty "launched a thousand ships," the authors interrogate whether beauty, once considered divine and ineffable, can now be assessed with scientific precision. Historical attempts to define beauty, from Polykleitos's canon to the golden ratio and Vitruvian symmetry, have shaped artistic and medical ideals. In plastic surgery, these concepts have been further formalized through cephalometric analyses and surgical guidelines. Contemporary tools, including the Marquardt Phi Mask, facial attractiveness scores, and deep learning models like those trained on SCUT-FBP5500, promise objective evaluations of beauty. Yet these algorithmic assessments-often validated through human raters or crowd-sourced platforms-reveal troubling limitations. They risk homogenizing aesthetic standards, marginalizing ethnic variation, and fostering unrealistic expectations in patients influenced by augmented reality filters and AI-driven ideals. While these metrics aid in reconstructive and aesthetic planning, they cannot encompass the cultural, emotional, or historical depth that beauty represents. The plastic surgeon now navigates between myth and machine, caught between ancient archetypes and algorithmic precision. Helen becomes not just a metaphor but a measurement-a reminder that beauty can be sought, approximated, even modified, but not fully captured. This paper argues that while measurement has its place, beauty ultimately resists full quantification. Between Aphrodite and algorithm lies the responsibility to treat not only form, but meaning-with empathy, imagination, and humility.
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http://dx.doi.org/10.1097/SCS.0000000000011542 | DOI Listing |
J Craniofac Surg
June 2025
Department of Plastic Surgery, Armed Forces Capital Hospital, Bundang-gu, Seongnam-City, Gyeonggi-do, and Department of Anatomy, College of Medicine, Ewha Womans University, Seoul, Republic of Korea.
This paper explores the evolving efforts to quantify beauty, tracing its path from mythological ideals to modern algorithms. Inspired by the legendary face of Helen of Troy-the mortal echo of Aphrodite-whose beauty "launched a thousand ships," the authors interrogate whether beauty, once considered divine and ineffable, can now be assessed with scientific precision. Historical attempts to define beauty, from Polykleitos's canon to the golden ratio and Vitruvian symmetry, have shaped artistic and medical ideals.
View Article and Find Full Text PDFEnviron Monit Assess
September 2023
Graduate School of Environmental Science, Hokkaido University, Sapporo, 060-0810, Japan.
Climate change and shifts in land use/land cover (LULC) are critical factors affecting the environmental, societal, and health landscapes, notably influencing the spread of infectious diseases. This study delves into the intricate relationships between climate change, LULC alterations, and the prevalence of vector-borne and waterborne diseases in Coimbatore district, Tamil Nadu, India, between 1985 and 2015. The research utilised Landsat-4, Landsat-5, and Landsat-8 data to generate LULC maps, applying the maximum likelihood algorithm to highlight significant transitions over the years.
View Article and Find Full Text PDFJ Agric Biol Environ Stat
September 2022
The University of Utah, Salt Lake City, USA.
The high mountain regions of Asia contain more glacial ice than anywhere on the planet outside of the polar regions. Because of the large population living in the Indus watershed region who are reliant on melt from these glaciers for fresh water, understanding the factors that affect glacial melt along with the impacts of climate change on the region is important for managing these natural resources. While there are multiple climate data products (e.
View Article and Find Full Text PDFMedicina (Kaunas)
December 2022
Clinical Medical College, Yangzhou University, Yangzhou 225009, China.
Background and Objectives: To evaluate the efficacy of bladder-prostatic muscle reconstruction and bladder neck eversion anastomosis in the recovery of urinary continence after robot-assisted radical prostatectomy (RARP). Materials and Methods: From January 2020 to May 2022, 69 patients who underwent RARP in our hospital were recruited. Thirty-seven patients underwent RARP with the Veil of Aphrodite technique (control group).
View Article and Find Full Text PDFJ Am Med Inform Assoc
June 2020
Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, California, USA.
Objective: Accurate electronic phenotyping is essential to support collaborative observational research. Supervised machine learning methods can be used to train phenotype classifiers in a high-throughput manner using imperfectly labeled data. We developed 10 phenotype classifiers using this approach and evaluated performance across multiple sites within the Observational Health Data Sciences and Informatics (OHDSI) network.
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