This study aims to develop a pan-cancer screening model using routine blood biomarkers (including complete blood count, biochemical tests, coagulation panel, and tumor markers). The study is retrospective, collecting data from approximately 10,000,000 cancer patients diagnosed at multiple centers in China between January 2006 and September 2025. All patients have confirmed pathological diagnosis and complete blood test records. A Mixture of Experts (MoE) machine learning model will be built to predict the presence of various cancers (e.g., gastric, colorectal, liver, lung, ovarian cancer). The goal is to establish a low-cost, non-invasive screening tool suitable for large-scale population screening.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Area under the ROC curve (AUC)
Timeframe: At study completion, approximately December 2030
Sensitivity of the model
Timeframe: At study completion, approximately December 2030
Specificity of the model
Timeframe: At study completion, approximately December 2030