Dual-energy CT-based deep learning radiomics can improve lymph node metastasis risk prediction for gastric cancer.
Jing LiDi DongMengjie FangRui WangJie TianHailiang LiPei-Jie LyuPublished in: European radiology (2020)
• This study investigated the value of deep learning dual-energy CT-based radiomics in predicting lymph node metastasis in gastric cancer. • The dual-energy CT-based radiomics nomogram outweighed the single-energy model and the clinical model. • The nomogram also exhibited a significant prognostic ability for patient survival and enriched radiomics studies.
Keyphrases
- lymph node metastasis
- dual energy
- deep learning
- computed tomography
- squamous cell carcinoma
- image quality
- papillary thyroid
- contrast enhanced
- artificial intelligence
- magnetic resonance imaging
- machine learning
- positron emission tomography
- convolutional neural network
- high resolution
- mass spectrometry
- case control
- single molecule