An Efficient Artificial Intelligence Based Technique in Diseases Staging and Forecasting

摘要: Artificial Intelligence (AI) techniques offer powerful objective algorithms for analysis of multimodal and high-dimensional data. Recently, these have become a reliable tool in the medical domain. This paper describes an efficient technique building application that is capable forecasting classifying healthcare information using machine learning as subfield AI methods. The algorithm predicts label each sample. sample single set feature data what category falls into. takes many samples training set, builds internal model finally labels other samples, called testing set. We apply this methodology to breast cancer staging also forecast myocardial infarction examine risk assessment fuzzy clustering Framingham heart study. results show proposed obtains credible outputs could be integrated used health care field.