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引用次数: 0
摘要
数字孪生技术正在成为慢性病管理中个性化医疗的变革范例。在本文中,我们将探讨数字孪生的概念和关键特征及其在慢性非传染性代谢性疾病管理中的应用,重点是糖尿病案例研究。我们介绍了各种类型的数字孪生模型,包括基于 ODE 的机理模型、数据驱动的 ML 算法以及结合两种方法优势的混合建模策略。我们介绍了成功的案例研究,展示了数字孪生子在改善 T1D 和 T2D 患者血糖结果方面的潜力,并讨论了将数字孪生子研究应用转化为临床实践的益处和挑战。
Digital twins and artificial intelligence in metabolic disease research.
Digital twin technology is emerging as a transformative paradigm for personalized medicine in the management of chronic conditions. In this article, we explore the concept and key characteristics of a digital twin and its applications in chronic non-communicable metabolic disease management, with a focus on diabetes case studies. We cover various types of digital twin models, including mechanistic models based on ODEs, data-driven ML algorithms, and hybrid modeling strategies that combine the strengths of both approaches. We present successful case studies demonstrating the potential of digital twins in improving glucose outcomes for individuals with T1D and T2D, and discuss the benefits and challenges of translating digital twin research applications to clinical practice.
期刊介绍:
Trends in Endocrinology and Metabolism (TEM) stands as a premier Reviews journal in the realms of metabolism and endocrinology. Our commitment is reflected in the publication of refined, concise, and highly impactful articles that delve into cutting-edge topics, encompassing basic, translational, and clinical aspects. From state-of-the-art treatments for endocrine diseases to groundbreaking developments in molecular biology, TEM provides comprehensive coverage.
Explore recent advancements in diabetes, endocrine diseases, obesity, neuroendocrinology, immunometabolism, molecular and cellular biology, and a myriad of other areas through our journal.
TEM serves as an invaluable resource for researchers, clinicians, lecturers, teachers, and students. Each monthly issue is anchored by Reviews and Opinion articles, with Reviews meticulously chronicling recent and significant developments, often contributed by leading researchers in specific fields. Opinion articles foster debate and hypotheses. Our shorter pieces include Science & Society, shedding light on issues at the intersection of science, society, and policy; Spotlights, which focus on exciting recent developments in the literature, and single-point hypotheses as Forum articles. We wholeheartedly welcome and encourage responses to previously published TEM content in the form of Letters.