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Cited by 365

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Department of Obstetrics and Gynecology

Open access
·2015·Juntendo Medical Journal

Abstract

Prediction of Preterm Birth Preterm birth is one of the major causes of neonatal death; thus, better diagnostics are necessary for the subsequent intensive care.However, it is still difficult to predict women who will develop preterm birth with high positive predictive value.Consequently, we have been investigating the possibility of maternal peripheral leukocytes as a marker to predict women with a risk of preterm labor using leukocyte migration assay, in collaboration with the University of Alberta, Canada. 2) Fetal Ischemic Brain InjuryFetal hypoxic ischemic encephalopathy is the leading cause of cerebral palsy, although the mechanism of cerebral palsy caused by fetal ischemia has not been elucidated yet.Collaborating with a group from the University of Gothenburg, Sweden, we are attempting to reveal the mechanism of ischemic cerebral palsy. 3) Novel Ultrasonographic TechniqueIt is important to diagnose the bleeding point on the uterine wall in patients with postpartum hemorrhage and to decide how to manage and treat it.We are developing a novel ultrasonographic imaging system using contrast media with the support of Hitachi Ltd.This new technique enables visualization of uterine bleeding at the bedside, which may be a more accurate and rapid modality for identification of the focus of intractable bleeding, leading to safer management of patients.As above, to improve maternal and fetal outcome during the perinatal and peripartum period, international joint research between industry and universities is currently being conducted.

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Metadata

Venue
Juntendo Medical Journal
Published
2015
Volume
61
Issue
3
Pages
322-323
ISSN
  • 0022-6769 (ISSN-L)
  • 2187-9737
  • 2188-2126
OpenAlex
W2582709257
Cited by
365
References
6
FWCI
5.05
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Department of Obstetrics and Gynecology. https://app.cochat.ai/papers/10.14789/jmj.61.322
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Department of Obstetrics and Gynecology. (2015). Juntendo Medical Journal. https://doi.org/10.14789/jmj.61.322

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.