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作者:

Xu, Yuhang (Xu, Yuhang.) | Liu, Haipeng (Liu, Haipeng.) | Hao, Dongmei (Hao, Dongmei.) | Taggart, Michael (Taggart, Michael.) | Zheng, Dingchang (Zheng, Dingchang.)

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摘要:

The relatively limited understanding of the physiology of uterine activation prevents us from achieving optimal clinical outcomes for managing serious pregnancy disorders such as preterm birth or uterine dystocia. There is increasing awareness that multi-scale computational modeling of the uterus is a promising approach for providing a qualitative and quantitative description of uterine physiology. The overarching objective of such approach is to coalesce previously fragmentary information into a predictive and testable model of uterine activity that, in turn, informs the development of new diagnostic and therapeutic approaches to these pressing clinical problems. This article assesses current progress towards this goal. We summarize the electrophysiological basis of uterine activation as presently understood and review recent research approaches to uterine modeling at different scales from single cell to tissue, whole organ and organism with particular focus on transformative data in the last decade. We describe the positives and limitations of these approaches, thereby identifying key gaps in our knowledge on which to focus, in parallel, future computational and biological research efforts.

关键词:

Surface reconstruction uterine activity uterine physiology Biological system modeling computational modeling Data models Pregnancy Uterus Computational modeling Physiology Biological systems

作者机构:

  • [ 1 ] [Xu, Yuhang]Coventry Univ, Ctr Intellignet Healthcare, Coventry CV1 5FB, W Midlands, England
  • [ 2 ] [Liu, Haipeng]Coventry Univ, Ctr Intellignet Healthcare, Coventry CV1 5FB, W Midlands, England
  • [ 3 ] [Zheng, Dingchang]Coventry Univ, Ctr Intellignet Healthcare, Coventry CV1 5FB, W Midlands, England
  • [ 4 ] [Hao, Dongmei]Beijing Univ Technol, Coll Life Sci & Bioengn, Beijing 100124, Peoples R China
  • [ 5 ] [Taggart, Michael]Newcastle Univ, Biosci Inst, Newcastle Upon Tyne NE1 3BZ, Tyne & Wear, England

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来源 :

IEEE REVIEWS IN BIOMEDICAL ENGINEERING

ISSN: 1937-3333

年份: 2022

卷: 15

页码: 341-353

1 7 . 6

JCR@2022

1 7 . 6 0 0

JCR@2022

JCR分区:1

中科院分区:2

被引次数:

WoS核心集被引频次: 3

SCOPUS被引频次: 3

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