Paper Key : IRJ************529
Author: Anjali.s,Amrutha.k.shaji,Sanjay.j,Blessy Rapheal.m
Date Published: 04 May 2023
Abstract
Lung cancer is a widespread disease that poses a significant challenge for radiologists to diagnose accurately. The early detection of lung cancer symptoms makes it possible to treat the disease effectively. With the latest advancements in computational intelligence, it is feasible to create a sustainable prototype model for treating lung cancer. However, researchers have been utilizing machine learning algorithms to develop smart computer-aided systems that can assist radiologists in making more precise diagnoses. The dataset is trained using various techniques, including SVC, K-Nearest Neighbour, Decision Tree, Logistic Regression, XgBoost, Gradient boosting and Random Forest. These models are implemented using python programming.
DOI LINK : 10.56726/IRJMETS37797 https://www.doi.org/10.56726/IRJMETS37797