Using public data to develop a model to predict PAD
Abstract In this analysis data from reliable public sources is analyzed. Moderning supervised machine learning techniques permit us to develop a method to predict who has Peripheral Arterial Disease (PAD) and assess the risk of death amongst these patients. As the data source is a robust database at the CDC website, that is representative of the population of United States of America, the mathematical model derived should better apply to those who reside in USA. This analysis