학술논문

A Deep Learning Based Approach to Predict Lung Cancer from Histopathological Images
Document Type
Conference
Source
2021 International Conference on Electronics, Communications and Information Technology (ICECIT) Electronics, Communications and Information Technology (ICECIT), 2021 International Conference on. :1-4 Sep, 2021
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Robotics and Control Systems
Signal Processing and Analysis
Deep learning
Machine learning algorithms
Computational modeling
Lung cancer
Lung
Predictive models
Cancer detection
lung cancer
deep learning
CNN
image processing
computer-aided diagnosis
Language
Abstract
Cancer is the deadliest disease in the world and Lung cancer is one of them. The number of deaths from lung cancer is much higher than the number of deaths from other cancers. In most cases, lung cancer is diagnosed at the last stage. To solve this problem currently, cancer is being diagnosed with the help of computer-assisted diagnostic systems. Cancer early detection and level prediction using a deep learning-based model is one of them. In this research, a deep learning model has been proposed which can perfectly detect and predict lung cancer levels from histopathological information. The model has been trained and validated using 15,000 lung cancer histopathological image data and has got 99.80% prediction accuracy from our model