It is reasonable to assume that well-performing ML models for healthcare can improve efficiency and speed up decision-making by delivering practical insights. These insights can be used to make better decisions based on historical data such as diseases, family history, and genetics disorders, among other things. The initial stages in building healthcare machine learning (ML) models are selecting the problem and establishing the prediction task. In this article, we will examine the requirements’