Machine Learning in Healthcare: Forecasting Patient Outcomes with Predictive Models

Abstract

Machine learning (ML) is rapidly transforming the healthcare landscape by offering powerful tools for predicting patient outcomes. From hospital readmissions to disease progression and survival rates, ML algorithms can utilize vast and complex datasets to uncover patterns and forecast future events. This paper discusses the application of various ML models in forecasting patient outcomes, evaluates their predictive accuracy, and highlights key challenges and future opportunities. The study aims to demonstrate how ML contributes to precision medicine and enhanced clinical decision-making.