基于数据挖掘的复发性流产证治规律研究

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中图分类号：R271；TP274

DOI：10.12339/j.issn.1673-8578.2026.01.032

Research on the Patterns of Diagnosis and Treatment for Recurrent Spontaneous Abortion Based on Data Mining//ZHANG Qi， WEI Fengqin

Abstract： This study employs literature data mining to analyze the clinical characteristics and medication patterns of recurrent abortion. Through computerized retrieval of China National Knowledge Infrastructure （CNKI） and application of inclusion/exclusion criteria， 449 relevant articles were identified. Statistical mining analysis of syndromes and medications was conducted using the cloud platform of ancient and modern medical records. Key syndromes identified include spleen-kidney deficiency and qi-blood deficiency syndrome， qi and blood deficiency syndrome. It is found that the deficiency syndrome is common， and the disease location involves kidney， spleen and liver， which follows the characteristics of strengthening the body resistance and eliminating evil， replenishing the congenital， and treating the liver， spleen and kidney together.

Keywords： recurrent spontaneous abortion; data mining; medical records; rule of diagnosis and treatment

复发性流产（recurrent spontaneous abortion， RSA），亦称为“数堕胎”“屡孕屡堕”，是指凡堕胎或小产连续发生3次或以上者，其发生率为 1%～5% [1]。（剩余3217字）