A revision of Traditional Chinese Medicine in the treatment of polycystic ovary syndrome: Utilizing data mining techniques for disease prevention and management

This study employed data mining to analyze clinical cases of polycystic ovary syndrome (PCOS), PCOS with insulin resistance (PCOS-IR), and insulin resistance (IR), examining their correlations and pathological evolution. A standardized repository was established by searching PubMed and additional medical databases for clinical cases of PCOS, PCOS-IR, and IR. Data mining identified 1,427 PCOS cases (364 Chinese herbal medicines; high-frequency drugs: Radix Angelicae Sinensis; key pairs: Fructus Rubi→Semen Cuscutae; 5 prescription clusters), 109 PCOS-IR cases (156 Chinese herbal medicines; high-frequency drugs: Poria; key pairs: Rhizoma Chuanxiong→Radix Angelicae Sinensis; 4 prescription clusters), and 68 IR cases (125 Chinese herbal medicines; high-frequency drugs: Poria; key pairs: Radix Bupleuri→Poria; 4 prescription clusters). The analysis also identified "Phlegm (dampness)" as a shared pathological factor across all conditions, crucially driving PCOS progression. These results suggested the distinct herbal patterns and clusters revealed both therapeutic commonalities and condition-specific strategies.