HDT systems generate virtual twins via deep phenotyping, i.e. Indeed, this HDT paradigm is a fundamental departure from traditional big data statistical techniques like logistic regressions. ICU IoT-enabled comprehensive physiological monitoring. The combination of AI, IoT, and CLO enables digital twins to offer predictive abilities beyond the traditional “predictor” technologies that currently exist, e.g. CLO is the use of this real-time data to monitor, diagnose, predict disease, and optimize treatment. CPS can be broken down into two components: (1) artificial intelligence (AI) systems that mimic human reasoning using big data processing and pattern recognition (2) Internet of Things (IoT) to facilitate rapid data synchronization between physical and digital twins. At the heart of HDT technology are two technical concepts: cyber-physical systems (CPS) and closed-loop optimization (CLO) 3. The authors define HDTs as a virtual representation (“digital twin”) of a patient (“physical twin”) that is generated from multimodal patient data, population data, and real-time updates on patient and environmental variables 2. They found growing activity in HDT-related innovation, including 18 patent applications, of which 73% were from companies and 27% were from academia 2. performed a mapping review of 88 papers related to HDT, with a particular focus on cardiovascular disease-related research.
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