Classificationof Stages of Lung Cancer using Genetic Candidate Group Search Approach
Manasee Kurkure, Anuradha Thakare · IOSR Journal of Computer Engineering · 2016
Cancer is one of the most commonly affected diseases in the progressing countries.Early diagnosis of cancer plays a significant role in curing cancer patients.Thousands of people every year die due to lung cancer, so there a need for accurate prediction of this disease.In this paper, a Genetic Candidate Group search algorithm approach is proposed.This optimization algorithm allows assistant doctors to identify the nodules present in the lungs at the early stages.As manual interpretations are time consuming and very critical, to overcome this difficulty this hybrid method is combined with Naïve Bayes Classification and different stages of cancer images fast and accurate.The number of images are tested and the results are obtained.The accuracy of 82 percentage is achieved in classification.