Multimodal MRI radiomics for predicting HIFU ablation efficacy in uterine fibroids: a machine learning study

Key Points

• To predict the efficacy of HIFU ablation using multimodal MRI and machine learning.
• Utilized multimodal MRI data and clinical features.
• Developed an XGBoost model for prediction.
• Applied machine learning techniques for analysis.
• The XGBoost model showed promise in predicting ablation efficacy.
• Optimized treatment strategies were suggested based on model outcomes.