Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to...

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Main Authors: Martin Becker, Jennifer Dai, Alan L. Chang, Dorien Feyaerts, Ina A. Stelzer, Miao Zhang, Eloise Berson, Geetha Saarunya, Davide De Francesco, Camilo Espinosa, Yeasul Kim, Ivana Marić, Samson Mataraso, Seyedeh Neelufar Payrovnaziri, Thanaphong Phongpreecha, Neal G. Ravindra, Sayane Shome, Yuqi Tan, Melan Thuraiappah, Lei Xue, Jonathan A. Mayo, Cecele C. Quaintance, Ana Laborde, Lucy S. King, Firdaus S. Dhabhar, Ian H. Gotlib, Ronald J. Wong, Martin S. Angst, Gary M. Shaw, David K. Stevenson, Brice Gaudilliere, Nima Aghaeepour
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-12-01
Series:Frontiers in Pediatrics
Subjects:
adverse pregnancy outcomes (APO)
psychosocial and stress-related factors
prediction
multitask machine learning
immune states
single-cell
Online Access:https://www.frontiersin.org/articles/10.3389/fped.2022.933266/full

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https://www.frontiersin.org/articles/10.3389/fped.2022.933266/full

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