Abstract
Due to the serious consequences of lung cancer, medical associations use computer-aided diagnostic procedures to diagnose this disease more accurately. Despite the damaging effects of lung cancer on the body, the lifetime of cancer patients can be extended by early diagnosis. Data mining techniques are practical in diagnosing lung cancer in its first stages. This paper surveys a number of leading data mining-based cancer diagnosis approaches. Moreover, this review draws a comparison between data mining approaches in terms of selection criteria and presents the advantages and disadvantages of each method.
Keywords: Lung cancer, machine learning, data mining algorithms, detection accuracy, dignosis, MRI.
Erratum In:
A Review on Lung Cancer Diagnosis Using Data Mining Algorithms
Graphical Abstract
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