Open AccessLiterature Survey for Lung Cancer Analysis and Prediction
Author(s) -
Gayathri Devi Nagalapuram,
D Varshashree,
Vansika Singh,
D Dheeraj,
Donal Jovian Nazareth,
Savitha B Hiremath
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40245
Subject(s) - lung cancer , convolutional neural network , computed tomography , stage (stratigraphy) , deep learning , artificial intelligence , cancer , artificial neural network , computer science , machine learning , medicine , radiology , oncology , paleontology , biology
Lung cancer is one of the most common and deadly cancers worldwide which can be cured only if it is discovered at an early stage. Lung cancer can be diagnosed using various technologies, including MRI, isotopes, X-rays, and CT. One of the most effective ways to fight cancer is to discover it early enough to significantly improve the patient's chances of survival which can be done by the means of Artificial Intelligence. The proposed approach uses past medical records to determine if the patient has lung cancer. The CT scans are analyzed by a Convolutional Neural Network (CNN) model to determine the stage of cancer. Finally, the suggested model would forecast the patient's estimated medical insurance costs. Machine learning (ML) and Deep Learning (DL) approaches will be used to train and test the models by utilizing open-source datasets. Keywords: Lung Cancer, Computed Tomography (CT) scans, Machine Learning (ML), Convolutional Neural Network (CNN), GoogLeNet.