Classification of breast cancer using microarray gene expression data: A survey - Abd-Elnaby, Muhammed; Alfonse, Marco; Roushdy, Mohamed (Journal of biomedical informatics, 2021)
Cancer, in particular breast cancer, is considered one of the most common causes of death worldwide according to the world health organization. For this reason, extensive research efforts have been done in the area of accurate and early diagnosis of cancer in order to increase the likelihood of cure. Among the available tools for diagnosing cancer, microarray technology has been proven to be effective. Microarray technology analyzes the expression level of thousands of genes simultaneously. Although the huge number of features or genes in the microarray data may seem advantageous, many of these features are irrelevant or redundant resulting in the deterioration of classification accuracy. To overcome this challenge, feature selection techniques are a mandatory preprocessing step before the classification process. In the paper, the main feature selection and classification techniques introduced in the literature for cancer (particularly breast cancer) are reviewed to improve the microarray-based classification.