학술논문

Classification of Lung Cancer Images Using Optimized Hybrid Deep Learning Model
Document Type
Conference
Source
2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT) Intelligent Data Communication Technologies and Internet of Things (IDCIoT), 2024 2nd International Conference on. :622-628 Jan, 2024
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Sensitivity
Pneumonia
Lung cancer
Lung
Genetics
Vaccines
Pollution measurement
ResNet
IAO
Gaussian Mixture
DCNN
Language
Abstract
This research study provides a concise overview of lung diseases, encompassing their diverse nature and impact on the respiratory system. Lung diseases can result from various factors, including genetics, environmental influences, and lifestyle choices. Diagnostic methods and treatment options are discussed, emphasizing the importance of early detection and a multifaceted approach to managing these conditions. Preventive measures, such as vaccination and smoking cessation, are very much vital in reducing lung diseases. This study serves as a valuable resource for those seeking a comprehensive understanding of these conditions and their management. The proposed model demonstrates impressive outcome with an accuracy level of 99.07%, a sensitivity level of 98.40%, a specificity level of 99.09%, a precision level of 98.11 %, and an Fl score of 97.94%.