ESCCPred is a prediction tool designed for early diagnosis of esophageal squamous cell carcinoma (ESCC). It utilizes machine learning algorithms to construct a diagnostic model based on serum autoantibodies. The model has been validated and shows promising performance with high accuracy, sensitivity, and specificity. The web-based interface of ESCCPred allows easy access to the diagnostic tool, providing a novel and serological method for early detection of ESCC.

https://litdong.shinyapps.io/ESCCPred/

Cite us!

TD Li, GY Sun, H Ye, et al. ESCCPred: A machine learning model for diagnostic prediction of early esophageal squamous cell carcinoma using autoantibody profiles(in preparation)

Contact:

Tiandong Li: litiandong@outlook.com