Development and validation of machine learning models for predicting synchronous lung metastasis in United States colorectal cancer patients: a SEER database analysis

CONCLUSIONS: Machine learning models, particularly XGB and RF, demonstrated robust performance in predicting synchronous CRCLM. CEA was consistently identified as the most important risk factor, supporting personalized chest CT utilization during initial CRC staging.