A Broad Review of AI and Machine Learning in Healthcare Informatics for Predictive Analytics, Data Analytics, and Healthcare Supply Chain Systems

Abstract

The healthcare informatics field is being transformed by Artificial Intelligence (AI) and Machine Learning (ML) that allow making decisions based on data, predictive analytics, and operating more efficiently. This literature review addresses the situation of the AI and ML in predictive analytics, data analytics, and healthcare supply chain management, with its possible benefits being the ones to improve patient outcomes, resource allocation optimization, and personalized care. It is mainly used in the early detection of diseases, risk stratification, population health management, and smart supply chain forecasting. Although these are beneficial, data quality, privacy, interoperability, ethical issues and biased algorithms are important challenges. New technologies, such as Explainable AI, federated learning, integration with the IoT, and block chain, will improve transparency, security, and efficiency. All in all, AI and ML play a role in the making of healthcare a proactive, patient-centered, and intelligent system.