Role of AI-Based Methods in Colorectal Cancer Diagnostics

Abstract

Colorectal cancer ranks as the second most prevalent cause of death, and proven to be a major cause of morbidity, where one in every six people worldwide dies from cancer. The early diagnostics have always been a torch bearing insight towards better and timely treatment, thus saving the life. In the recent, advanced medical technology has facilitated large amounts of variable data set for analysis, whereas artificial intelligence (AI) technology has the proven role in automatic cancer detection, enabling us to analyze more patients in less time and money hence, commonly used in oncology. The convolutional neural network based models have been quite popular to evaluate cancer imaginary data in current scenario. In this chapter, the authors summarize the computational resources, basic architecture, and applications of advanced AI based methods / soft computing methodologies; i.e. machine learning, deep learning, CNN, RNN, SVM and other machine learning methods for early and faster diagnostics of colorectal cancer with imaginary classification of patient data with challenges.

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