Cited by 11Pregnancy and preeclampsia studiesArtificial Intelligence in HealthcareArtificial Intelligence in Healthcare and Education

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Doppler Ultrasound Imaging Combined with Fetal Heart Detection in Predicting Fetal Distress in Pregnancy-Induced Hypertension under the Guidance of Artificial Intelligence Algorithm

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Liu, Su, Sun, Yue, Luo, Na·2021·Journal of Healthcare Engineering

Abstract

This study was to improve the feasibility and economic benefits of intelligent medical system Doppler ultrasound (DUS) imaging technology combined with fetal heart detection to predict the fetal distress in pregnancy-induced hypertension (PIH), so as to reduce the risk of deterioration of the patient’s condition. The characteristics of DUS images were analyzed, and a diffusion filter reducing the specificity was adopted to improve the smooth speckle noise of DUS images. 120 pregnant women in hospital were the subjects of the study, all of whom received ultrasound cord blood flow testing and fetal heart monitoring. 88 PIH patients with fetal distress were diagnosed and included in the observation group, and 32 healthy pregnant women tested during the same period were identified as the control group. Clinical data were reviewed and analyzed. The diagnostic rates of fetal distress by simple fetal heart monitoring and DUS detection combined with fetal heart monitoring were compared. The results showed that 26.7% of fetal distress were diagnosed by fetal heart monitoring alone, and 73.3% of fetal distress were diagnosed by combined testing, so the diagnostic accuracy of the combined detection method was greatly higher than the single fetal heart detection ( P < 0.05 ). The Pulsatility index (PI), resistance index (RI), and S/D values detected by the umbilical artery in the observation group were 1.48, 0.85, and 4.31, respectively. The PI, RI, and S/D values detected by the umbilical artery in the control group were 0.96, 0.64, and 3.59, respectively. The results of arterial detection were significantly higher than those of the control group, and the difference was of significant scientific significance ( P < 0.05 ). In summary, the PI and RI values of the middle cerebral artery (MCA) detected by DUS diagnosis can effectively reflect the current status of the fetus in the uterus and reduce the mortality of the fetus. The images guided by DUS imaging technology can clearly show the current status of the fetus in the uterus, effectively improve the medical diagnostic efficiency, and have important reference value for the development of intelligent medical equipment.

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References 21 · Cited by 11

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Metadata

Authors
Liu, S., Sun, Y., & Luo, N.
Affiliations
Qiqihar Medical University (CN)
Corresponding author
Luo, Na
Venue
Journal of Healthcare Engineering
Publisher
Wiley
Published
2021-10-08
Volume
2021
Pages
1-10
ISSN
  • 2040-2295 (ISSN-L)
  • 2040-2309
OpenAlex
W3203832790
Cited by
11
References
21
Citations by year
2025: 1 · 2024: 3 · 2023: 4 · 2022: 3
FWCI
2.27
Type
journal article
Language
en
Status
Retracted
Open access
Locations
  • Journal of Healthcare Engineering (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
Joint Guidance Project of Science and Technology Plan of Qiqihar (LHYD-2021052)
Topics
  • Health Sciences › Medicine › Obstetrics and Gynecology › Pregnancy and preeclampsia studies
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
Doppler ultrasound, gestational hypertension, umbilical artery Doppler, middle cerebral artery Doppler, pulsatility index, resistance index, S/D ratio, speckle reduction, fetal heart rate monitoring, fetal well-being
MeSH terms
Artificial Intelligence, Blood Flow Velocity, Female, Fetal Distress, Fetal Heart, Humans, Pregnancy, Umbilical Arteries, Ultrasonography, Prenatal, Ultrasonography, Doppler, Hypertension, Pregnancy-Induced

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CoChat. (2026). Citation check: Doppler Ultrasound Imaging Combined with Fetal Heart Detection in Predicting Fetal Distress in Pregnancy-Induced Hypertension under the Guidance of Artificial Intelligence Algorithm. https://app.cochat.ai/papers/10.1155/2021/4405189
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Liu, S., Sun, Y., & Luo, N. (2021). Doppler Ultrasound Imaging Combined with Fetal Heart Detection in Predicting Fetal Distress in Pregnancy-Induced Hypertension under the Guidance of Artificial Intelligence Algorithm. Journal of Healthcare Engineering. https://doi.org/10.1155/2021/4405189