Serum CST4 and routine laboratory indicators data for gastrointestinal tumor SVM diagnostic model

This dataset supports the research titled "Serum Cystatin 4 Combined with Routine Clinical Laboratory Indicators: A Support Vector Machine Diagnostic Model for Early Screening of Gastrointestinal Tumors". It includes clinical laboratory data from 344 subjects, consisting of 214 patients with pathologically confirmed gastrointestinal tumors (91 gastric cancer, 80 colorectal cancer, 43 esophageal cancer) and 130 non-tumor individuals who underwent physical examinations at the same institution between January 2022 and June 2025. The dataset contains 38 laboratory indicators per subject, including 14 blood routine parameters (e.g., white blood cell count [WBC], hematocrit [HCT], platelet count [PLT]), 16 biochemical indicators (e.g., total protein [TP], albumin [ALB]), 8 traditional tumor markers (e.g., carcinoembryonic antigen [CEA], carbohydrate antigen 50 [CA50]), and serum cystatin 4 (CST4) detected by enzyme-linked immunosorbent assay (ELISA). All data have undergone preprocessing, including mean imputation for missing values and Z-score method (|Z|>3) for outlier handling to ensure data quality. This dataset serves as the foundational data for constructing and validating machine learning-based diagnostic models for early gastrointestinal tumor screening. Researchers can use it to reproduce the support vector machine (SVM) model developed in the study, compare the performance of different algorithms, or explore additional predictive biomarkers. Detailed variable definitions, preprocessing protocols, and usage guidelines are provided in the accompanying README file.