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.