Department of Computer Science and Electrical Engineering, Institute for Visual and Analytic Computing, Universität Rostock, Albert-Einstein-Straße 22, 18059 Rostock, Germany.
Department of Pathology, University of California San Diego, GPL/CMM-West, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Clin Perinatol. 2024 Jun;51(2):345-360. doi: 10.1016/j.clp.2024.02.003. Epub 2024 Mar 15.
Multiple studies have hinted at a complex connection between maternal stress and preterm birth (PTB). This article describes the potential of computational methods to provide new insights into this relationship. For this, we outline existing approaches for stress assessments and various data modalities available for profiling stress responses, and review studies that sought either to establish a connection between stress and PTB or to predict PTB based on stress-related factors. Finally, we summarize the challenges of computational methods, highlighting potential future research directions within this field.
多项研究表明,母体压力与早产(PTB)之间存在复杂的联系。本文描述了计算方法在研究这种关系方面的潜力。为此,我们概述了现有的压力评估方法以及可用于描述压力反应的各种数据模态,并回顾了那些试图建立压力与 PTB 之间联系或根据与压力相关的因素预测 PTB 的研究。最后,我们总结了计算方法的挑战,突出了该领域潜在的未来研究方向。