Healthcare Predictive Analytics using Machine Learning

Abstract

Predictive analytics in health care leverages machine learning (ML) techniques to analyze historical data and predict future outcomes. This enhances decision-making and patient care. This abstract reviews various ML methods employed in health care predictive analytics. These include regression analysis decision trees, support vector machines neural networks and ensemble methods. These techniques are applied to predict patient outcomes. Also disease progression, hospital readmissions and treatment responses. Integration of ML in health care promises significant improvements in both accuracy and efficiency. However, challenges such as data privacy integration with existing systems and model interpretability need to be addressed. This is necessary to fully realize its potential.