Artificial Neural Networks (ANNs) in Lungs Cancer Detection

Abstract

The research looks into the use of an Artificial Neural Network model to detect the presence of lung cancer in someone's body. We developed an Artificial Neural Network (ANN) in this paper to detect the presence or absence of lung cancer in the human body. Symptoms such as yellow fingers, anxiety, chronic disease, fatigue, allergy, and wheezing, coughing, shortness of breath, swallowing difficulty, and chest pain were used to diagnose lung cancer. They were used as input variables for our ANN, along with other information about the person. Our ANN was created, trained, and validated using the data set "survey lung cancer." The ANN model was found to be 96.67 percent accurate in detecting the absence or presence of lung cancer.