AI and Digital Twins in Healthcare: Revolutionizing Remote Patient Monitoring and Precision Medicine

Pairing artificial intelligence (AI) with digital twin technology is transforming healthcare by providing real time remote patient monitoring and pushing precision medicine forward. In this study we explore the potential of AI driven digital twins to improve patient outcomes, reduce costs and increase efficiency in healthcare. To accomplish this, the research focuses on developing AI algorithms to monitor and predict patient health remotely, which tackles those major challenges to be able to intervene in time and provide individualized care. The paper accounts for current knowledge of AI using a data driven approach by reviewing existing literature and recent developments and through case studies of practical applications of AI in patient management. Data analysis techniques were then methodologically combined with ethical considerations of using patient data in order to obtain accurate and private patient data. This key finding shows that with the combination of predictive AI algorithms and digital twins of the patient, diagnostic power can be improved and treatments personalised – to the benefit of the patient. This research is novel for its outlook on how AI can contribute to the building of such responsive, real time digital twins for healthcare. Based on the study’s implications, the adoption of digital twin technology together with AI holds promise to redesign the future of healthcare where diagnostic accuracy is enhanced and healthcare facilities are rendered a lighter burden. These insights are vital for doctors, policy makers and researchers working towards a leading role for AI in patient centric care models.