The DOI matches its Crossref record; the references it cites are not checked yet.
Doppler Ultrasound Imaging Combined with Fetal Heart Detection in Predicting Fetal Distress in Pregnancy-Induced Hypertension under the Guidance of Artificial Intelligence Algorithm
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“Lastly, Liu et al. proposed a Doppler US model for the prediction of fetal distress in women with pregnancy-induced hypertension [169].”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
The citation lists haven’t been fetched yet
References 21 · Cited by 11
Research works printed but not linked: 20
- 10.1016/j.ajogmf.2020.100107 · DOI
- 10.1016/j.preghy.2018.06.008 · DOI
- 10.1097/MD.0000000000004863 · DOI · Paper page
- 10.1186/s12884-016-0954-4 · DOI
- 10.3389/fendo.2018.00546 · DOI
- 10.3389/fendo.2019.00163 · DOI
- 10.1371/journal.pone.0221719 · DOI
- 10.1080/14767058.2018.1441278 · DOI
- 10.1088/1361-6579/aaa925 · DOI
- 10.1007/s10278-018-0132-5 · DOI
- 10.1155/2018/2413637 · DOI
- 10.1016/j.tjog.2018.11.034 · DOI
- 10.1002/uog.20224 · DOI
- 10.1016/j.cca.2017.09.018 · DOI
- 10.1080/14767058.2017.1401605 · DOI
- 10.3760/cma.j.issn.0529-567X.2017.03.003 · DOI
- 10.1080/14767058.2018.1450380 · DOI
- 10.1016/j.ejrad.2011.11.056 · DOI
- 10.1002/uog.20125 · DOI
- 10.1080/14767058.2019.1575804 · DOI
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
- PMC
- PMC8519722
- 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
- Update notices
- retraction (2023-10-11)
- Open access
- hybrid
- doi.org
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- 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
- The paper
- 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