A k-NN method for lung cancer prognosis with the use of a genetic algorithm for feature selection

作者：

Highlights：

• A KNN algorithm is employed for diagnosing the stage of lung cancer disease.

• A genetic algorithm is hybridized for an efficient feature selection.

• The best value for K is determined using an experimental procedure.

• The implementation on a long cancer database reveals 100% accuracy.

• The proposed approach requires the least CPU time among four.

摘要

•A KNN algorithm is employed for diagnosing the stage of lung cancer disease.•A genetic algorithm is hybridized for an efficient feature selection.•The best value for K is determined using an experimental procedure.•The implementation on a long cancer database reveals 100% accuracy.•The proposed approach requires the least CPU time among four.

论文关键词：Lung cancer,Cancer staging diagnosis,Data mining,Genetic algorithm,Feature selection,k-NN technique

论文评审过程：Received 6 July 2019, Revised 4 September 2020, Accepted 7 September 2020, Available online 11 September 2020, Version of Record 21 September 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113981