Abstract: Diseases affect our daily lives as a result of most people's lifestyles. In the health-care field, most person's data is analysed as per the sickness that has impacted them as a result of their lifestyle, and some info is hidden that will be valuable in making good decisions. In this research, we use people's lifestyle disorders to process and analyse data using machine learning algorithms, and we use data visualization techniques to predict disease stage using machine learning algorithms Decision tree and K-Nearest Neighbour algorithm. And depending on that training data, we need to perform data validation to forecast the results. And with the dataset we can collect electronic medical records; all the medical record patient details are available as well as precision. The proposed model will help preserve the lives of the majority of patients, and we will be able to avoid the majority of incurable diseases if we can identify causes early on.

In the medical field, machine learning can be used for diagnosis, detection and prediction of various diseases. The main goal of this paper is to provide a tool for doctors to detect Lung Cancer disease at early stage. This in turn will help to provide effective treatment to patients and avoid severe consequences.

Keywords: Disease, machine learning, Lung Cancer, K-Nearest Neighbour algorithm

| DOI: 10.17148/IARJSET.2022.96145