Esophageal cancer is a common malignant tumor worldwide, characterized by late-stage detection, diverse histological types, and significant regional differences. Early diagnosis remains challenging in basic medical institutions due to limited resource and the lack of comprehensive patient information. To address these issues, we developed an intelligent pre-consultation system specifically for esophageal cancer. The system integrates an evidence - based medical knowledge graph for esophageal cancer, which serves as a foundation for clinical decision-making. By combining this knowledge graph with artificial intelligence technology, the system facilitates pre - consultation provide patients and clinicians with detailed and accurate information. After patients schedule an appointment through the intelligent pre - consultation system, their medical history is automatically collected via mobile terminals and synchronized with the outpatient doctor's workstation. This process enables the automatic generation of electronic medical records, providing doctors with immediate access to comprehensive patient data for precise and efficient consultations. The system improves the early screening and diagnostic accuracy of esophageal cancer, streamlines the diagnosis and treatment workflow, and enhances the overall quality of care. By leveraging advanced AI technologies and evidence-based medical knowledge, this innovation addresses critical challenges in esophageal cancer management and aims to improve patient outcome.

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