JSAI2020

Presentation information

International Session

International Session » E-2 Machine learning

[1K5-ES-2] Machine learning: Social application (2)

Tue. Jun 9, 2020 5:20 PM - 6:40 PM Room K (jsai2020online-11)

Chair; Hisashi Kashima (Kyoto University)

6:20 PM - 6:40 PM

[1K5-ES-2-04] Blockchain-and AI-Based Female Genital Cosmetic Surgery (FGCS): Beyond a Mechanistic View of Sexual Satisfaction

〇Wen Hsien Ethan Huang1, Tien Ten Hsu1, Hui Chin Chang1 (1. GeneHope Medical Aesthetics Group)

Keywords:Female genital cosmetic surgery, FGCS, AI, Blockchain

Background: The issue of asking for and provisioning of FCGS is essentially a matter of individual patient and physician decision-making. Advancement of blockchain and artificial intelligence (AI) capabilities in cosmetic medicine can now help address many pressing problems and the algorithm will further improve with user engagement. Methods: A deep convolutional neural network (DCNN) was trained using a dataset of 2010 clinical images obtained from 350 female patients for assessment of genital rejuvenation from May 2018 to Jun 2019. The proposed system consists of an intelligent recognition device, an app running either on an iPhone or Android-based mobile device, a deep learning training server, and a cloud-based management platform encrypted with blockchain-secured communication channel. Results: The Artificial Intelligence recognized the classification of a patient with an accuracy of 0.94 and a correlation between manual and automatized evaluation of r = 0.95 (P less than .001). Conclusion: Here the new concept makes machine-to-beauty readability possible by linking AI and blockchain technology. Humans and machines working together are always much more powerful than either alone. Further technical work is needed to add additional functions.

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