Research on Innovative Application of Medical Vertical Large Model Driven by Dynamic Reordering Technology

Abstract:
With the increasing application of artificial intelligence technology in the medical field, the medical vertical large model has become the core support for auxiliary disease diagnosis, treatment and prognosis evaluation. However, the current medical big model landing faces multiple pain points such as data fragmentation, model ' illusion ', and insufficient application adaptability. This study focuses on the integration and innovation of dynamic reordering technology and medical vertical big model, and constructs a 'data+technology+application' trinity solution. Through the cross-disciplinary knowledge fusion system, the data problem is solved, and the dynamic reordering algorithm is introduced to suppress the ' illusion '. After multi-scenario optimization and multi-dimensional verification, the safe and credible application of the model in scenarios such as esophageal cancer is promoted. The research results provide technical support for the transformation of medical intelligence and practical reference for improving the efficiency and quality of clinical diagnosis and treatment.