Machine learning predictive model based on the corneal biomechanics of clinical data

The optimized SVM model provides a reliable, data-driven approach for individualized ectasia-risk assessment in refractive surgery. By combining biomechanical and tomographic features, it enables early identification of high-risk patients and supports personalized surgical planning and postoperative monitoring. Further multi-center and long-term validation is warranted to enhance generalizability and clinical implementation.