Revolutionizing gastrointestinal cancer research with artificial intelligence: From precision patient stratification to real-world evidence

Figure 3 Multimodal data integration and artificial intelligence-powered clinical application framework in gastrointestinal oncology. This diagram presents a structured framework for the integration of artificial intelligence (AI) in gastrointestinal cancer management. I: Multimodal data input includes clinical data, medical imaging, pathology slides, molecular biomarkers (e.g., HER2, MSI, PD-L1), and real-world data from electronic health records and wearable devices; II: The AI model layer incorporates deep learning, radiomics, machine learning, and federated learning to construct robust and privacy-preserving predictive models; III: Output applications span patient stratification, drug dose optimization, individualized treatment planning, and regulatory compliance—illustrating the translational path from data acquisition to clinical deployment.