Our study identified key predictive factors for DLNM and elucidated significant prognostic indicators for HCC patients with DLNM. These findings provide clinicians with valuable tools to accurately identify high-risk individuals for DLNM and conduct more precise risk stratification for this patient subgroup, potentially improving management strategies and patient outcomes.
Keyphrases
- lymph node metastasis
- machine learning
- end stage renal disease
- squamous cell carcinoma
- ejection fraction
- newly diagnosed
- chronic kidney disease
- big data
- papillary thyroid
- case report
- palliative care
- artificial intelligence
- clinical trial
- electronic health record
- type diabetes
- patient reported outcomes
- deep learning
- insulin resistance
- weight loss
- glycemic control