AI-Enhanced Intelligent Healthcare: Advancements in Remote Monitoring, Predictive Analytics and Disease Diagnosis

Abstract

Artificial Intelligence (AI) and Deep Learning (DL) in healthcare have brought advanced health monitoring and predictive analytics. By amalgamating AI with the IoT, Remote Healthcare Monitoring (RHM) systems have been generated, allowing the constant monitoring of patients’ health statuses along with decreasing healthcare expenditures. In this paper, we analyze AI-based healthcare innovations exerting their impact in modern medical practices and the need for more advancement in the healthcare predictive solutions from the perspective of AI and the role AI plays in healthcare, that is, the applications of AI in healthcare like disease diagnosis, biomedical research, and predictive analytics. Weather Clinical Decision Support Systems (CDSS) use AI to make specific therapy suggestions based on patient’s characteristics and facilitate the best outcomes. Additionally, AI smart city healthcare systems provide effective solutions for remote applications and in improving smart city urban healthcare services. There have been recent advancements in deep learning being used to accurately identify deep learning through Convolutional Neural Networks (CNNs) and predictive modeling of chronic diseases. While AI increases healthcare efficiency and precision to a great extent, existing issues such as data privacy, model interpretability, and system integration still exist. Further studies should focus on further improving natural language processing (NLP) and the adaptability of the AI models along with looking into ethical issues before the widespread usage of AI can be allowed.