We developed a preoperative predictive machine-learning model using deep transfer learning, radiomics, and clinical features to differentiate LNM status in CRC, aiding in treatment decision-making for patients.
Keyphrases
- positron emission tomography
- computed tomography
- lymph node metastasis
- machine learning
- deep learning
- end stage renal disease
- decision making
- pet ct
- pet imaging
- squamous cell carcinoma
- patients undergoing
- ejection fraction
- magnetic resonance imaging
- chronic kidney disease
- contrast enhanced
- newly diagnosed
- artificial intelligence
- prognostic factors
- peritoneal dialysis
- magnetic resonance
- dual energy
- image quality