دورية أكاديمية
A framework towards digital twins for type 2 diabetes
| العنوان: | A framework towards digital twins for type 2 diabetes |
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| المؤلفون: | Yue Zhang, Guangrong Qin, Boris Aguilar, Noa Rappaport, James T. Yurkovich, Lance Pflieger, Sui Huang, Leroy Hood, Ilya Shmulevich |
| المصدر: | Frontiers in Digital Health, Vol 6 (2024) |
| بيانات النشر: | Frontiers Media S.A., 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Medicine LCC:Public aspects of medicine LCC:Electronic computers. Computer science |
| مصطلحات موضوعية: | digital twin, type 2 diabetes, knowledge graph, machine learning, precision medicine, Medicine, Public aspects of medicine, RA1-1270, Electronic computers. Computer science, QA75.5-76.95 |
| الوصف: | IntroductionA digital twin is a virtual representation of a patient's disease, facilitating real-time monitoring, analysis, and simulation. This enables the prediction of disease progression, optimization of care delivery, and improvement of outcomes.MethodsHere, we introduce a digital twin framework for type 2 diabetes (T2D) that integrates machine learning with multiomic data, knowledge graphs, and mechanistic models. By analyzing a substantial multiomic and clinical dataset, we constructed predictive machine learning models to forecast disease progression. Furthermore, knowledge graphs were employed to elucidate and contextualize multiomic–disease relationships.Results and discussionOur findings not only reaffirm known targetable disease components but also spotlight novel ones, unveiled through this integrated approach. The versatile components presented in this study can be incorporated into a digital twin system, enhancing our grasp of diseases and propelling the advancement of precision medicine. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2673-253X |
| العلاقة: | https://www.frontiersin.org/articles/10.3389/fdgth.2024.1336050/fullTest; https://doaj.org/toc/2673-253XTest |
| DOI: | 10.3389/fdgth.2024.1336050 |
| الوصول الحر: | https://doaj.org/article/42febbed3fe641b9be4078e0077dd232Test |
| رقم الانضمام: | edsdoj.42febbed3fe641b9be4078e0077dd232 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 2673253X |
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| DOI: | 10.3389/fdgth.2024.1336050 |