An intelligent decision support system for the accurate diagnosis of cervical cancer
作者：
Highlights：
• Decision support system for accurate diagnosis of cervical cancer from risk factors.
• Oversampling or undersampling alone fails to provide satisfactory performance.
• Novel hybrid sampling technique is introduced to address high imbalance in the data.
• Crucial risk factors are identified using GA to enhance performance.
• Combining hybrid sampling with GA provides a robust decision support system.
摘要
•Decision support system for accurate diagnosis of cervical cancer from risk factors.•Oversampling or undersampling alone fails to provide satisfactory performance.•Novel hybrid sampling technique is introduced to address high imbalance in the data.•Crucial risk factors are identified using GA to enhance performance.•Combining hybrid sampling with GA provides a robust decision support system.
论文关键词：Machine learning,Decision support system,Cervical cancer,Genetic algorithm,SMOTE
论文评审过程：Received 26 July 2021, Revised 18 March 2022, Accepted 19 March 2022, Available online 25 March 2022, Version of Record 8 April 2022.
论文官网地址：https://doi.org/10.1016/j.knosys.2022.108634
