Introducing automated system for Lung Cancer Detection using Evolutionary Approach

Cancer is one of the most commonly affected diseases in the developed countries. Early diagnosis plays a significant role in curing cancer patients. Every year, thousands of people die due to Lung cancer. In this paper, a novel Candidate group search algorithm based on evolutionary 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. Genetic algorithm (GA) helps in identifying genes that help to classify patient lung cancer status with notable predictive performance. Keywords— Data Clustering, Genetic Algorithm, Naïve Bayes Classification, Candidate Group Search algorithm, Canny Edge Detection Algorithm, Optimization.