基于机器学习算法的宫颈癌辅助诊断模型

Keyphrases

• Cervical Cancer 100%
• Machine Learning Algorithms 100%
• Cervical Cancer Diagnosis 100%
• Assistant Diagnosis 100%
• Machine Learning Models 66%
• Validation Set 33%
• Children's Health 33%
• Clinical Role 33%
• Affiliated Hospitals 33%
• Clinical Setting 33%
• Clinical Value 33%
• CIN2+ 33%
• Area under the Curve 33%
• Predictive Models 33%
• Performance Prediction 33%
• Training Set 33%
• Maternal Health 33%
• Model-based Diagnosis 33%
• Neural Network 33%
• Cervical Lesions 33%
• Cervical Intraepithelial Neoplasia Grade 2 33%
• Decision Tree Model 33%
• Central Hospitals 33%
• Cervical Intraepithelial Neoplasia Grade 1 33%
• Chengdu 33%
• Neural Network Model 33%
• Qingdao 33%
• K-fold Cross-validation 33%
• Risk Predictive Model 33%

Pharmacology, Toxicology and Pharmaceutical Science

• Uterine Cervix Cancer 100%
• Uterine Cervix Carcinoma in Situ 50%
• Cross-Validation 25%