Healthcare Data Handling with Machine Learning Systems: A Framework

Data collected in healthcare can be categorized and structured in ways that resemble big data. Analyzing big healthcare data with machine learning (ML) is one of the most effective methods. Using different learning models, ML can assist in the prediction of diseases and the timely diagnosis of patients, improving their health. The use of ML in healthcare data analytics, however, must be preceded by an understanding of which learning model to employ. Choosing between a variety of models to healthcare data becomes a challenge when applying machine learning. The purpose of this paper is to provide a framework for identifying the best machine-learning model for healthcare data.