[Application and challenges of the clinical decision support system in hematological diseases].

Abstract

Hematological diseases, particularly hematological neoplasms, are highly heterogeneous, characterized by diverse clinical manifestations and complex biological features. Clinical Decision Support System (CDSS) is an auxiliary diagnosis and treatment system that integrates clinical data, medical expertise, and artificial intelligence (AI), which is expected to significantly improve the standardization, accuracy, and efficiency of diagnosis and treatment for hematological diseases and thereby improve prognosis. This review aimed to systematically summarize the application status of CDSS in hematological diseases, discuss its core value, analyze the current challenges, and outline future development. CDSS has potential in standardized diagnosis and treatment, accurate diagnosis and treatment, early prevention, and efficiency improvement of hematological diseases, including hematological neoplasms and bleeding and coagulation disorders. However, it faces many challenges, such as data processing, knowledge base construction and maintenance, model performance optimization, system integration, and a lack of evaluation criteria. In the future, CDSS is expected to integrate multicenter and multimodal data to enable precise, individualized, and whole-process hematological disease management.