Digital Health Transformation: Leveraging AI for Monitoring and Disease Management

Background and aim: The integration of artificial intelligence (AI) is causing a significant upheaval in the landscape of digital health. By utilizing AI, this development aims to improve disease monitoring and management, ushering in a new era of healthcare. This article's goal is to examine how AI is transforming illness management and monitoring, which will ultimately improve patient outcomes.
Methods: To study the complex effects of AI on disease monitoring and management, a thorough examination of contemporary research and case studies from the actual world was carried out. The process includes examining a variety of sources, including reports on healthcare technologies, clinical trials, and research papers.
Results: The application of AI technologies, such as machine learning and predictive analytics, to the processes of illness monitoring and management has produced outstanding results. These results include improved patient adherence to treatment regimens, tailored treatment recommendations, and more timely and accurate disease detection. Additionally, AI-driven remote monitoring systems make it possible to collect data in real-time, improving healthcare providers' capacity to decide wisely and take preventative measures.
Conclusion: Healthcare could undergo a major transformation as a result of the use of AI to illness monitoring and management. It gives patients and healthcare professionals more control, resulting in more accurate diagnoses, customized treatment plans, and better patient outcomes. Healthcare will become more patient-centered and data-driven in the future, opening up new possibilities for improved illness management.