Unlocking Prospects of Digital Twin in Healthcare

This article discusses the application of artificial intelligence and digital twin technology with a focus on its use in healthcare and individualized treatment planning. Deep AI methods like convolutional neural networks and hybrid mathematical models facilitate dynamic, predictive virtual patient modeling, allowing anatomical segmentation, landmark detection, and treatment simulation with improved accuracy and efficiency. Substantial advancements are observed in various domains of medical science with multimodal imaging and real-time data integration. The work also assesses new ideas like blockchain-secured data management and the metaverse, with implications for data security and operational efficiency. Technical, clinical, and regulatory challenges are critically discussed, with recommendations for standardized protocols, AI applications, and effective privacy measures. The paper intends to explore AI-augmented digital twin platforms synergizing individualized, predictive, and preventive patient management, while shaping their responsible and feasible use in the clinical environment.