Abstract
Colon cancer detection is a great significant task in medical diagnosis. the detection ofcolorectal cancer in an early stage can significantly facilitate clinicians' decision-making and reducemortality. The accurate detection results help to explore symptomatic treatment promptly; this can beachieved by using automatic systems with histopathological images. The combination of convolutionalneural networks and supervised machine learning methods are used to achieve better classificationresults than using individual pre-trained deep networks. Therefore, this study is aimed to get a highperformance and accuracy of CNN combined them with supervised machine learning methods. SupportVector Machine (SVM), decision tree (DT) and k-nearest neighbour (KNN) as the classification ofcolon cancer to get the best accuracy (PDF) A Hybrid Machine Learning Techniques with Deep Neural Network Model for Colon Cancer Diagnosis. Available from: https://www.researchgate.net/publication/381480941_A_Hybrid_Machine_Learning_Techniques_with_Deep_Neural_Network_Model_for_Colon_Cancer_Diagnosis#fullTextFileContent [accessed May 03 2025].