An Empirical Investigation of the Use of Artificial Neural Networks (ANN) for Lung Cancer Disease Diagnosis

Lung cancer is one of the “causes of death in developing countries”, and it is on the rise as a result of the massive raise in smoking tobacco. Tumours, immune response dysfunction, and other problems caused by cancerous cells can obstruct the body’s ability to function normally. Lung cancer is an abnormal tumour of the lungs that causes unregulated tumour growth in the organs. The “Artificial Neural Network or ANN” is utilised to detect the existence of lung cancer in the human body. ANN is a brand-new “Machine Learning (ML)” methodology that works with both small and large samples. An “artificial neural network (ANN)” is a statistical model based on the structure and performance of “natural neural networks In neural networks, there are input and output levels, as well as hidden layer that turn the input into something that the output unit can use (in most circumstances). The major purpose of this study is to use characteristics, which are a set of human features and data, to indicate the existence of lung cancer cells. The study investigates if an Artificial Neural Network framework can be used to detect the existence of lung cancer in a person’s body. Both primary quantitative and secondary qualitative research methods are considered to develop in depth analysis.