Smart Health Care Management System for Diagnosis of Lungs Cancer

Document Type

Conference Proceeding

Source of Publication

2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN)

Publication Date

7-7-2023

Abstract

Lung cancer has a mortality rate that is significantly greater than other forms of cancer, making it the second biggest cause of death worldwide after cardiovascular disease. Detecting lung cancer in its earliest stages has been the focus of a significant amount of research and development over the past few years, leading to the development of several unique computer-aided diagnostic tools that use deep learning. On the other hand, deep learning models are readily susceptible to overfitting, and this issue invariably results in decreased performance. In this study, we proposed a CNN-based approach for the classification of lung cancer and attained 95.62% accuracy. When applied to classifying lung cancer, the solution achieves the most outstanding performance possible throughout the entire dataset. The overfitting issue that arises during lung cancer classification tasks may be solved with the help of the proposed framework, which also outperforms existing methods that are considered to be state-of-the-art.

ISBN

979-8-3503-3538-5

Publisher

IEEE

Volume

00

First Page

401

Last Page

405

Disciplines

Computer Sciences

Keywords

Deep learning, Smart healthcare, Neural networks, Lung cancer, Lung, Production, Convolutional neural networks

Indexed in Scopus

no

Open Access

no

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