Cutting-edge artificial intelligence applications are transforming oncological diagnostics by improving the precision and prediction of tumor characteristics. Notably, researchers have developed a deep learning framework named MSI-SEER for accurate identification of microsatellite instability-high tumors and their response to immune checkpoint inhibitors. Additionally, AI models predict dynamic carcinoembryonic antigen levels to refine gastric cancer prognosis. These innovations leverage digital pathology and multimodal data integration to advance personalized medicine in oncology.