Forecasting Healthcare Results in Rural and Resource-Limited Settings Using the Machine Learning Algorithm

Abstract

In this research, we investigate machine learning (ML) application in the healthcare domain we predict obesity, perinatal mortality, diabetes risk assessment, and how to integrate blockchain into healthcare. It shows ML promising to increase disease prediction, optimize the policies of healthcare, and secure the data. ML is highly predictive accurately though it suffers from interpretability and fairness challenges. To achieve the equitable healthcare outcomes, future works need to develop better models for causal inference and embed the ethics in the process.