Noninvasive prediction of renal fibrous capsule invasion in RCC is rather difficult by abdominal CT images before surgery. A machine learning classifier integrated with radiomics features shows a promising potential to assist surgical treatment options for RCC patients.
Keyphrases
- contrast enhanced
- machine learning
- end stage renal disease
- computed tomography
- image quality
- cell migration
- dual energy
- minimally invasive
- ejection fraction
- newly diagnosed
- renal cell carcinoma
- chronic kidney disease
- deep learning
- magnetic resonance imaging
- prognostic factors
- positron emission tomography
- magnetic resonance
- patients undergoing
- coronary artery bypass
- optical coherence tomography
- convolutional neural network
- big data
- climate change
- human health
- patient reported outcomes