Farzad Heydari and Marjan Kuchaki Rafsanjani* Pages 1 - 11 ( 11 )
Due to the serious consequences of lung cancer, medical associations are using computer-aided diagnostic procedures to more accurately diagnose cancer. In spite of the damaging consequences of lung cancer on the body, the lifetime of cancerous people can be extended by early diagnosis. Data mining techniques are practical ways to diagnose lung cancer at its first stages. This paper surveys a number of main data mining based cancer diagnosis approaches. Moreover, this research draws a comparison between data mining approaches in terms of selection criteria and presents the advantages and disadvantages of each method.
Lung cancer, Machine learning, Data mining algorithms, Detection accuracy, Dignosis, Accuracy
Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman