Artificial neural networks for diagnosis and survival prediction in colon cancer

Abstract

ANNs are nonlinear regression computational devices that have been used for over 45 years in classification and survival prediction in several biomedical systems, including colon cancer. Described in this article is the theory behind the three-layer free forward artificial neural networks with backpropagation error, which is widely used in biomedical fields, and a methodological approach to its application for cancer research, as exemplified by colon cancer. Review of the literature shows that applications of these networks have improved the accuracy of colon cancer classification and survival prediction when compared to other statistical or clinicopathological methods. Accuracy, however, must be exercised when designing, using and publishing biomedical results employing machine-learning devices such as ANNs in worldwide literature in order to enhance confidence in the quality and reliability of reported data.

Presenting a Model for Periodontal Disease Diagnosis Using Two Artificial Neural Network Algorithms

“…ANNs are used to help physicians in disease diagnosis for the past five decades. NNs attracted especial attention due to their ability to learn complex issues, along with the ability to maintain accuracy, even in the absence of some information (22,23). Computational accuracy is an important tool used when applying an NN to ensure the quality of the final results (24).…”

The role of capillary electrophoresis–mass spectrometry to proteome analysis and biomarker discovery

“…SVMs provide a tool to overcome some of these limitations due to the theoretical principles upon which they are based [98]. An ANN approach utilizes all available data set to find ideal separating features and can also be used for classification [99] as has been reported for analysis of breast cancer [100] and hepatocellular carcinoma [101].…”

Artificial Neural Network Modeling and Simulation of In-Vitro<SUB>Nanoparticle-Cell</SUB><SUB> Interactions</SUB>

“…17 Ahmed's review showed that applications of ANNs have improved the accuracy of colon cancer classification and survival prediction compared to other mathematical or clinicopathological methods. 18 As a result, ANN appears to be an appropriate approach for modeling complex input-output relationships in medicine.…”