Analysis of Risk Factors for Cervical Cancer Based on Machine Learning Methods
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/8681058/8691125/08691126.pdf?arnumber=8691126
Cited by 32 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Comprehensive analysis of artificial intelligence techniques for gynaecological cancer: symptoms identification, prognosis and prediction;Artificial Intelligence Review;2024-07-29
2. Predictive modeling and web-based tool for cervical cancer risk assessment: A comparative study of machine learning models;MethodsX;2024-06
3. Performance Comparison of XGBoost and LightGBM Gradient Boosting Algorithms in Predicting Cervical Cancer Risk;2024 International Conference on Computing and Data Science (ICCDS);2024-04-26
4. A Novel Web Framework for Cervical Cancer Detection System: A Machine Learning Breakthrough;IEEE Access;2024
5. Classification and detection of cervical cancer for enhancement diagnosis rate using XGBoost algorithm in comparison with artificial neural network;AIP Conference Proceedings;2024
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