Hematological indicator-based machine learning models for preoperative prediction of lymph node metastasis in cervical cancer - Zhao, Huan; Wang, Yuling; Sun, Yilin; Wang, Yongqiang; Shi, Bo; Liu, Jian; Zhang, Sai (Frontiers in Oncology, 2024)
accuracy (0.831, 95% CI: 0.702-0.960), specificity (0.835, 95% CI: 0.708-0.962), sensitivity (0.831, 95% CI: 0.702-0.960), and F1-score (0.829, 95% CI: 0.696-0.962). RF had the highest AUC in the testing set (AUC = 0.854).RF based on preoperative hematological indicators that are easily available in clinical practice showed superior performance in the preoperative prediction of CC LNM.However, investigations on larger external cohorts of patients are required for further validation of our findings.