Artificial Intelligence in Real-World Healthcare: A Theoretical Study on AI-Based Patient Monitoring Systems
Abstract
The integration of AI technology within the health sector has brought about a technological revolution through intelligent data analytics, intelligent decision-making, and intelligent monitoring of patients. There has been an increased amount of data generated due to the integration of electronic medical records, wearable devices, biomedical sensors, and the Internet of Medical Things (IoMT). Intelligent healthcare systems that make use of AI technology can continuously capture data about patients and provide intelligent analytics on the state of their health. This theoretical research work examines the importance of the application of AI technology in health care with regard to intelligent monitoring of patients through AI technology. The utilization of AI systems for patient monitoring offers various benefits, including constant observation, disease prediction, personalized healthcare suggestions, clinical workload reduction, and patient safety. Such systems may be applied in critical care monitoring, chronic disease management, remote healthcare services, and preventive healthcare. Nevertheless, there exist some barriers to implementation, such as the protection of patients' data, cyber threats, ethical issues, explainability of AI models, poor data quality, and regulation. The research contributes to a better understanding of AI-based patient monitoring systems and emphasises the importance of implementing such systems for creating future healthcare environments. The results of the research show that the combination of artificial intelligence and healthcare technology allows the provision of efficient, predictive, and patient-centered medical services. Further improvements of explainable AI systems, data management, and personalized intelligent healthcare are expected in the future.