New Method for Lung Cancer Prediction

New Method for Lung Cancer Prediction

 
New Method for Lung Cancer Prediction

Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features

An experimental comparison of artificial neural network (ANN) and support vector machine (SVM) ensembles and their “nonensemble” variants for lung cancer prediction by Covenant University’s Dr. Emmanuel Adetiba and Professor Oludayo O. Olugbara of Durban University of Technology, showed that the result of the ANN ensemble and HOG genomic features is promising for automated screening and early detection of lung cancer.

The researchers in their study titled, ‘Lung Cancer Prediction Using Neural Network Ensemble with Histogram of Oriented Gradient Genomic Features’, said the proposed framework has several advantages, which include automated prediction using artificial neural network ensemble, multiple biomarkers for lung cancer on a single platform, compliance with NGS genomic-based technology, and high prediction accuracy.

The performance comparison of the proposed framework with support vector machine and local binary pattern is valuable for decision makers to consider tradeoffs in method accuracy versus method complexity, they said.

Click here for more