Machine learning-based clinical decision support tool for advanced ESCC in the immunotherapy era: a multi-center study - PubMed
2 hours ago
- #Machine Learning
- #Clinical Decision Support
- #ESCC Prognosis
- Machine learning models were developed to support clinical decisions for treatment-naive advanced esophageal squamous cell carcinoma (ESCC).
- A random survival forest model using Boruta feature selection showed the highest predictive performance for overall survival at 6-, 12-, and 18-month intervals.
- The model was validated across multiple centers, demonstrated good calibration and clinical utility, and is available via a web calculator for personalized prognosis.