Multi-Modal AI Plastic Surgery Diagnosis and Decision-Making System: Integration of Deep Learning and Psychological Assessment

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Abstract

Purpose : To design and develop an AI-based plastic surgery recommendation system using 3D photographs and psychological questionnaire surveys, aiming to provide personalized treatment solutions for the plastic surgery industry. Methods : Based on artificial intelligence technology, this study utilized patients' 3D photographs and psychological questionnaire results as training samples to construct a personalized AI-based plastic surgery recommendation system. This system comprehensively considers factors such as patients' anxiety levels, economic status, and psychological expectations. The study selected 5,543 cases of plastic surgery outpatients aged 18 to 55 years, collected their 3D photographs and questionnaire data, and used these for AI system training. The software predicted treatment projects and compared them with doctors' predictions to validate the system's accuracy and patient satisfaction. Third-party doctors evaluated the system's safety, ultimately developing an efficient and accurate plastic surgery recommendation system. Results : The economic downturn in the post-COVID-19 era significantly impacted psychological health and the plastic surgery industry. Factors such as age, education level, income, and gender had significant effects on patients' psychological state and treatment willingness. The AI system integrated patients' psychological state, gender, income, and physical characteristics, providing personalized plastic surgery treatment suggestions and achieving a 93.25% patient satisfaction rate. Conclusion : The AI-based personalized plastic surgery recommendation system offers an innovative solution for the industry, enhancing the accuracy of treatment suggestions and patient satisfaction, thereby promoting sustainable development. In the post-pandemic era, the plastic surgery industry should focus on patients' physical, psychological, and economic factors to achieve personalized services.

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