U.S., July 2 -- ClinicalTrials.gov registry received information related to the study (NCT07045181) titled 'Prediction Model of Pancreatic Neoplasms in CP Patients With Focal Pancreatic Lesions' on June 22.
Brief Summary: This study aims to develop XGBoost machine learning model to predict pancreatic neoplasms in CP patients with focal pancreatic lesions.
Study Start Date: July 01
Study Type: OBSERVATIONAL
Condition:
Chronic Pancreatitis
Pancreatic Neoplasm
Machine Learning
Intervention:
DIAGNOSTIC_TEST: XGBoost machine learning
XGBoost is a powerful machine learning algorithm known for its efficiency and performance. It is an optimized gradient boosting library designed to be highly efficient, flexible, and portable. XGBoost works ...