Therapy and Diagnosis of Cancer Techniques: A Review

The aim of this paper is to put forth steps to kindle research interest in health care. Health care with artificial intelligence (AI) techniques brings about the e-health system. This research article comprises cancer diagnosis and therapy using AI techniques. Mutations and AI can be applied over the problems to get the end result. The article also shows the techniques used in the diagnosis and therapy of cancer. The graph network particles are passed over the human body. The images are captured and stored in the database as a dataset. This can act as an input for the pre-processing stage. Features extraction is the next step. The neural network is used as a classifier to classify the abnormal and normal cells. Finally, this acts as an input for predictions of other patients. This is an eye-opening article on the advancements in the health care system. This paper describes the research methodologies that can be applied over the detection of the cancer cells. To study the research methodologies that can be applied over the detection of the cancer cells. This paper presents the two major classification algorithms for predicting cancer. Based on the experimental results, the decision tree and neural network classifiers improve the accuracy in the detection of cancer. The results obtained by comparing the decision tree and the artificial neural network (ANN) show that the ANN gives better accuracy than the decision tree. The datasets collected are pre-processed and the respective features are extracted from the dataset. Based on the experimental results, the ANN classifier gives a better outcome than the decision tree.