Using machine learning to predict cervical lymph node metastasis on dual-energy CT
In this article, we extracted “hand-crafted” radiomic features from dual-energy CT (DECT) virtual monochromatic images (VMIs) reconstructed at different energies and used machine learning to construct prediction models that use the radiomic features of head and neck squamous cell carcinoma (HNSCC) to predict associated nodal metastases. This proof of concept study demonstrated that (1) HNSCC radiomic features can predict associated