The research aims to develop a machine learning-based tool for personalized risk assessments in advanced esophageal squamous cell carcinoma (ESCC).
Utilized the Boruta-RSF model incorporating available clinical variables.
Developed a web calculator for user-friendly prognostic assessments.
Conducted the study across multiple centers to ensure diverse data.
The tool significantly improved personalized prognostic assessments.
Optimized treatment strategies based on individual risk profiles.
Resumen
The Boruta-RSF model, leveraging routinely available clinical variables with the corresponding web calculator, facilitates personalized prognostic assessment and optimization of treatment strategies.