An Interpretable Machine Learning Model With Synthetic MRI ‐Based Habitat Radiomics for Predicting Lymph Node Metastasis in Oral Cancer

Key Points

• This research aims to enhance predictive accuracy for lymph node metastasis in oral cancer using a machine learning model.
• Used synthetic MRI-derived T1 and T2 maps to create a radiomics signature.
• Developed a machine learning model to analyze the radiomics data.
• Compared the model's accuracy against traditional clinical diagnosis.
• The machine learning model showed better predictive accuracy than clinical diagnosis.
• The radiomics signature provided meaningful insights into metastasis prediction.