Data Analytics in Healthcare Informatics: A Review of Artificial Intelligence and Machine Learning for Predictive Healthcare and Supply Chain Management

Abstract

This review examines the disruptive nature of data analytics, Artificial Intelligence (AI) and machine learning (ML) in healthcare informatics, namely predictive healthcare and the supply chain. It emphasizes that AI and ML allow preempting diseases, risk classification in the patient, individual therapy, and operating efficiently by implementing predictive analytics. In real-world practices, there is an increase in the accuracy of the diagnosis, allocation resources, and optimization of inventory. Other issues discussed in the paper include data privacy, algorithmic bias, interoperability and ethical issues. The future of healthcare systems has new trends such as IoT integration, precision medicine, smart healthcare ecosystems, and explainable AI, which provide a chance to develop proactive, patient-centered, and efficient healthcare systems.