The concept of Digital Twins (DTs), software models that mimic the behavior and interactions of physical or conceptual objects within their environments, has gained traction in recent years, particularly in medicine and healthcare research. DTs technology emerges as a pivotal tool in disease modeling, integrating diverse data sources to computationally model dynamic biological systems. This narrative review explores potential DT applications in medicine, from defining DTs and their history to constructing DTs, modeling biologically relevant systems, as well as discussing the benefits, risks, and challenges in their application. The influence of DTs extends beyond healthcare and can revolutionize healthcare management, drug development, clinical trials, and various biomedical research fields.
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http://dx.doi.org/10.1109/OJEMB.2024.3426916 | DOI Listing |
Clin Transl Allergy
January 2025
Department of Otorhinolaryngology & Clinical Allergy Center, The First Affiliated Hospital, Nanjing Medical University, Nanjing, China.
Background: Digital health, digital medicine, and digital therapeutics integrate advanced computer technologies into healthcare, aiming to improve efficiency and patient outcomes. These technologies offer innovative solutions for the management of allergic diseases, which affect a significant proportion of the global population and are increasing in prevalence. BODY: This review examines the current progress and future potential of digital health in allergic disease management.
View Article and Find Full Text PDFPart 2 explores the transformative potential of artificial intelligence (AI) in addressing the complexities of headache disorders through innovative approaches, including digital twin models, wearable healthcare technologies and biosensors, and AI-driven drug discovery. Digital twins, as dynamic digital representations of patients, offer opportunities for personalized headache management by integrating diverse datasets such as neuroimaging, multiomics, and wearable sensor data to advance headache research, optimize treatment, and enable virtual trials. In addition, AI-driven wearable devices equipped with next-generation biosensors combined with multi-agent chatbots could enable real-time physiological and biochemical monitoring, diagnosing, facilitating early headache attack forecasting and prevention, disease tracking, and personalized interventions.
View Article and Find Full Text PDFMar Pollut Bull
December 2024
Institute for Water and Wastewater Technology, Durban University of Technology, Durban-4001, South Africa. Electronic address:
Recent advancements in data analytics, predictive modeling, and optimization have highlighted the potential of integrating algal blooms (ABs) with Industry 4.0 technologies. Among these innovations, digital twins (DT) have gained prominence, driven by the rapid development of artificial intelligence (AI) and machine learning (ML) technologies, particularly those associated with the Internet of Things (IoT).
View Article and Find Full Text PDFMed Image Anal
December 2024
University Hospital Zurich and University of Zurich, Center for Translational and Experimental Cardiology, Zürich, Switzerland.
Transthoracic Echocardiography (TTE) is a crucial tool for assessing cardiac morphology and function quickly and non-invasively without ionising radiation. However, the examination is subject to intra- and inter-user variability and recordings are often limited to 2D imaging and assessments of end-diastolic and end-systolic volumes. We have developed a novel, fully automated machine learning-based framework to generate a personalised 4D (3D plus time) model of the left ventricular (LV) blood pool with high temporal resolution.
View Article and Find Full Text PDFJ Environ Manage
December 2024
School of Geography and Environment & Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang, 330022, China. Electronic address:
The human geographical environment is a comprehensive setting formed by the interaction between human activities and the geographical environment, characterized by its complexity and vulnerability. Applying the digital twin method to create a new research model in a human geographical environment holds significant academic and practical value. This approach helps avoid disturbances in the real environment, deeply explores complex issues, and optimizes solutions for real-world geographical problems.
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