Multimodal AI System for Plastic Surgery Diagnosis and Decision-Making Using Deep Learning of Psychological...

Area of Science:

• Artificial Intelligence in Medicine
• Plastic Surgery Innovations
• Digital Health Solutions

Background:

• The post-COVID-19 economic downturn has impacted mental health and the plastic surgery sector.
• Patient decisions in plastic surgery are influenced by psychological state, economic factors, and personal expectations.

Purpose of the Study:

• To develop an Artificial Intelligence (AI)-based plastic surgery recommendation system.
• To provide personalized treatment solutions for the plastic surgery industry using 3D photographs and psychological surveys.

Main Methods:

• Trained an AI system using 3D photographs and psychological questionnaire data from 5543 plastic surgery outpatients (aged 18-55).
• The AI system integrated patient psychological state, gender, income, and physical characteristics for personalized suggestions.
• Validated the AI system's accuracy and patient satisfaction by comparing its predictions with physician predictions and through third-party evaluations.

Main Results:

• The AI system achieved a 93.25% patient satisfaction rate.
• AI recommendations demonstrated accuracy and safety comparable to those of physicians.
• The system demonstrated potential to enhance clinical decision-making efficiency in plastic surgery.

Conclusions:

• The AI-based personalized plastic surgery recommendation system enhances treatment accuracy and patient satisfaction.
• The system promotes sustainable development in the plastic surgery industry through personalized services.
• Future plastic surgery approaches should integrate physical, psychological, and economic patient factors, especially in the post-pandemic era.