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Lung Cancer Detection from X-Ray Images using Hybrid Deep Learning Technique

V. Sreeprada, K. Vedavathi

2023Procedia Computer Science24 citationsDOIOpen Access PDF

Abstract

This article explore lung cancer using a hybrid deep learning (DL) model. Thus, this article offers a hybrid CNN along with the SVM classification method with tuned hyperparameters, which is the orthogonal Convolution neural network-support vector machine OCNN-SVM model. Each lung image may be automatically categorized and analyzed by this system to determine whether cancer cells are present. CNN has fewer parameters and is easier to train than a fully linked network with an exact count of hidden units. SVM has also been used to remove irrelevant data that has an adverse effect on accuracy. The effectiveness of this method is assessed in this research, and the findings show that the proposed orthogonal Convolution neural network-support vector machine (OCNN-SVM) model has been successful in categorizing lung images.

Topics & Concepts

Support vector machineComputer scienceHyperparameterConvolutional neural networkArtificial intelligenceConvolution (computer science)Deep learningPattern recognition (psychology)Artificial neural networkMachine learningCOVID-19 diagnosis using AILung Cancer Diagnosis and TreatmentRadiomics and Machine Learning in Medical Imaging
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