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Currently, deep learning techniques are utilized to diagnose and prognosis the tumors' localization in histopathology images. Globally, Colon cancer (CRC) is the third leading cause of cancer-related death. An intelligent computer-based colon cancer diagnosis is developed by using various Deep Learning (DL) techniques. Early detection of colon tumors is vital for good treatment and diagnosis. Early detection of cancer activities before treatment is significantly important in medical trials or personalizing tumor treatments. Hereditary colorectal cancers can be generally divided into two types such as hereditary non-polyposis colon cancer as well as familial anomalous polyposis. The early detection of colon cancer can increase the patient's survival rate. This research focused on predicting and analyzing colorectal cancer data using deep learning methods. This comprehensive research supports researchers in accomplishing an effective solution for colorectal cancer. At present, deep learning methodologies are commonly employed to enhance the precision of tumor localization in histopathology image analysis and to optimize cancer classification.
Srivani et al. (Fri,) studied this question.