Development of a serum protein biomarker panel for the diagnosis of pancreatic ductal adenocarcinoma using a machine learning approach.

ABSTRACT: Early detection of pancreatic ductal adenocarcinoma (PDA) remains a major clinical challenge due to the lack of reliable biomarkers. We developed and validated a machine learning (ML)-based serum protein biomarker panel to enhance PDA diagnosis. Serum concentrations of 47 protein biomarkers were measured in 355 individuals using a Luminex™ bead-based immunoassay. Multiple ML algorithms were employed to construct a diagnostic model, with SHapley Additive exPlanations (SHAP) analysis used to determine the importance of each biomarker. The diagnostic performance of the panel was assessed by the area under the receiver operating characteristic curve (AUROC), F1 score, sensitivity, specificity, and accuracy, and further validated in an independent cohort of 130 individuals. Among the tested mod

SUBMITTER: Shin DW 

PROVIDER: S-EPMC12518602 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature