AI Risk Assessment Model for Complication Prevention in Plastic Surgery (Artificial Intelligence)

The goal of this observational study is to determine if an AI-based risk assessment model can help prevent complications in plastic surgery patients by improving decision-making, providing recommendations to address risk factors, and assisting doctors in choosing the optimal timing and setting for elective plastic surgery. The study aims to answer if the AI model can effectively identify high-risk patients and what specific risk factors predict complications. Purpose: Evaluate the clinical effectiveness of an AI-based risk assessment model in preventing complications in plastic surgery patients by analyzing clinical data and patient history, providing personalized recommendations to mitigate risk factors and enhance outcomes. Hypothesis: The AI model can more accurately identify high-risk patients and provide effective recommendations to reduce complications compared to traditional methods. Participants: Individuals undergoing elective plastic surgery. They will complete an online form collecting data on age, height, weight, smoking habits, and comorbidities. The system calculates risk scores, BMI, and Caprini scores. Study Procedures: Risk assessment using the AI model, which evaluates multiple factors and generates personalized recommendations, including weight management, smoking cessation, blood pressure control, Doppler ultrasound for DVT, nutritional consultations, and specialist referrals. Recommendations are reviewed and approved by plastic surgeons. Follow-Up: The follow-up period ranges from 2 to 41 months, with a mean of 15 months. Data on patient outcomes, including complication rates and satisfaction, will be collected and analyzed. Outcomes Measured: Incidence of complications, the accuracy of the AI model in predicting complications, and its impact on improving surgical outcomes. Impact: The study aims to provide insights into AI use in plastic surgery, leading to better risk assessment tools and protocols, enhancing preoperative plannin