Computers in Industry, Год журнала: 2024, Номер 164, С. 104181 - 104181
Опубликована: Сен. 21, 2024
Язык: Английский
Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 111105 - 111105
Опубликована: Апрель 1, 2025
Язык: Английский
Процитировано
0
International Journal of Innovative Research in Computer Science & Technology, Год журнала: 2025, Номер 13(1), С. 19 - 25
Опубликована: Янв. 1, 2025
The rapid evolution of healthcare technology has led to innovative solutions for addressing challenges in patient care, operational efficiency, and data management. Among these, cloud-based digital twins have emerged as a transformative technology, offering real-time, data-driven models that mirror physical entities such patients, medical devices, or processes. This comprehensive review explores the integration twin with cloud computing industry, highlighting its potential revolutionize monitoring management practices. Cloud infrastructure enables seamless collection, storage, processing vast amounts data, empowering provide real-time insights into health, predictive diagnostics, personalized treatment plans. Furthermore, examines role optimizing hospital workflows, improving efficiency enabling remote monitoring. Key security, interoperability, computational demands integrating existing systems are discussed alongside solutions. study also outlines current applications emerging trends, emphasizing artificial intelligence machine learning enhancing capabilities twins. Ultimately, this underscores fostering patient-centric, ecosystem, paving way smarter more efficient delivery systems.
Язык: Английский
Процитировано
0
Smart Health, Год журнала: 2025, Номер unknown, С. 100541 - 100541
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
0
Elsevier eBooks, Год журнала: 2025, Номер unknown, С. 511 - 528
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Journal of Translational Medicine, Год журнала: 2025, Номер 23(1)
Опубликована: Март 19, 2025
As global cancer incidence and mortality rise, digital twin technology in precision medicine offers new opportunities for treatment. This study aims to systematically analyze the current applications, research trends, challenges of tumor therapy, while exploring future directions. Relevant literature up 2024 was retrieved from PubMed, Web Science, other databases. Data visualization performed using R VOSviewer software. The analysis includes initiation funding models, distribution, sample size analysis, data processing artificial intelligence applications. Furthermore, investigates specific applications effectiveness diagnosis, treatment decision-making, prognosis prediction, personalized management. Since 2020, on oncology has surged, with significant contributions United States, Germany, Switzerland, China. Funding primarily comes government agencies, particularly National Institutes Health U.S. Sample reveals that large-sample studies have greater clinical reliability, small-sample emphasize validation. In integration medical imaging, multi-omics data, AI algorithms is key. By combining multimodal dynamic modeling, accuracy models been significantly improved. However, different types still faces related tool interoperability limited standardization. Specific shown advantages surgical planning. Digital holds substantial promise therapy by optimizing plans through integrated modeling. factors such as language restrictions, potential selection bias, relatively small number published this emerging field, which may affect comprehensiveness generalizability our findings. Moreover, issues heterogeneity, technical integration, privacy ethics continue impede its broader application. Future should promote international collaboration, establish unified interdisciplinary standards, strengthen ethical regulations accelerate translation
Язык: Английский
Процитировано
0
Computers in Industry, Год журнала: 2024, Номер 164, С. 104181 - 104181
Опубликована: Сен. 21, 2024
Язык: Английский
Процитировано
1