Generative artificial intelligence-driven medical digital twin technologies in blockchain Internet of Things wearable sensor and computer vision-based extended reality healthcare metaverse

The research problem of this paper was whether medical image, behavioral pattern, and physiological data analysis further artificial intelligence-based disease progression prediction, big medical data analysis and processing, and treatment planning optimization, digital twin- and generative artificial intelligence-based disease progression prediction and medical process simulation, patient outcome and pathological condition improvement, and medical service efficiency and resource allocation. We show that physiological measurement indicator modeling and simulation and patient diagnosis and clinical workflow optimization necessitate generative artificial intelligence- and machine learning-based metaverse wearable and implantable medical devices. Our analyses debate on medical metaverse digital twin generative artificial intelligence and machine learning-based big clinical and medical imaging data interoperability and analysis harnessed in remote medical treatment and healthcare practices, healthcare delivery and patient outcome enhancement, real-time medical anomaly detection, timely medical treatment and response prediction, and immersive medical procedure and healthcare delivery simulation in blockchain Internet of Things wearable sensor and computer vision-based extended reality healthcare metaverse. Our results and contributions clarify that clinical decision support systems and generative artificial intelligence-based patient medical disease and health data processing and analysis configure clinical patient care and outcome prediction, health risk forecasting, medical abnormality detection, and remote patient vital sign and health issue monitoring.