Lung Cancer detection using Deep Learning

TL;DR

This paper presents a hybrid deep learning approach combining CNNs and SVMs for early lung cancer detection from CT scans, aiming to improve accuracy in distinguishing benign and malignant tumors.

Contribution

It introduces a novel hybrid model that leverages CNNs and SVMs for improved early lung cancer detection from CT scan data.

Findings

Hybrid model achieves high accuracy in tumor classification.

Deep learning enhances early detection capabilities.

Method demonstrates potential for clinical application.

Abstract

In this paper we discuss lung cancer detection using hybrid model of Convolutional-Neural-Networks (CNNs) and Support-Vector-Machines-(SVMs) in order to gain early detection of tumors, benign or malignant. The work uses this hybrid model by training upon the Computed Tomography scans (CT scans) as dataset. Using deep learning for detecting lung cancer early is a cutting-edge method.