Diagnosing Cervical Cancer Using Machine Learning Methods
Author:
Affiliation:
1. Institute of Graduate Studies, Altinbaş University,İstanbul,Turkey
2. AltinbaşUniversity,Software Engineering,İstanbul,Turkey
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9799780/9799803/09800033.pdf?arnumber=9800033
Reference15 articles.
1. Cervical Cancer Identification with Synthetic Minority Oversampling Technique and PCA Analysis using Random Forest Classifier
2. Data-Driven Cervical Cancer Prediction Model with Outlier Detection and Over-Sampling Methods
3. Machine learning for assisting cervical cancer diagnosis: An ensemble approach
4. Optimization of Decision Tree Machine Learning Strategy in Data Analysis
5. Random forest (machine learning)
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2. Expert System Techniques in Intelligent Diagnostic Digital Cytopathology System for Cervical Intraepithelial Neoplasia Detection;2023 4th International Conference on Innovative Trends in Information Technology (ICITIIT);2023-02-11
3. A Novel and Effective method for Early Identification of Cervical Cancer based on Gradient Boosting Classifier;2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF);2023-01-05
4. An Optimized Machine learning model for Automatic Prediction of Cervical Cancer Using Decision Tree Classifier;2022 International Conference on Computer, Power and Communications (ICCPC);2022-12-14
5. A Review: Various Challenges and Causes based on Cervical Cancer;2022 5th International Conference on Contemporary Computing and Informatics (IC3I);2022-12-14
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