Evidence map›Paper›PMID 34868516›Full record

ArticleJournal of healthcare engineering2021

Artificial Intelligence Algorithm-Based Analysis of Ultrasonic Imaging Features for Diagnosis of Pregnancy Complicated with Brain Tumor.

Lin Wu, Donghui Wei, Ning Yang, Hong Lei, Yun Wang

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Observational
  5. Ultrasound of Fetal Cardiac Function Changes in Pregnancy-Induced Hypertension Syndrome.Evidence-based complementary and alternative medicine : eCAM · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Lin WuDepartment of Gynaecology, The Centre Hospital Weinan, Weinan 714000, Shaanxi, China.ORCID 0000-0002-8121-9260
Donghui WeiDepartment of Neurosurgery, The Centre Hospital Weinan, Weinan 714000, Shaanxi, China.ORCID 0000-0003-4093-4660
Ning YangDepartment of Gynaecology, The Centre Hospital Weinan, Weinan 714000, Shaanxi, China.ORCID 0000-0003-3292-9028
Hong LeiDepartment of Gynaecology, The Centre Hospital Weinan, Weinan 714000, Shaanxi, China.ORCID 0000-0002-9839-3257
Yun WangDepartment of Neurosurgery, The Centre Hospital Weinan, Weinan 714000, Shaanxi, China.ORCID 0000-0003-2195-0294
Weinan Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research was to explore the accuracy of ultrasonic diagnosis based on artificial intelligence algorithm in the diagnosis of pregnancy complicated with brain tumors. In this study, 18 patients with pregnancy complicated with brain tumor confirmed by pathology were selected as the research object. Ultrasound contrast based on artificial bee colony algorithm was performed and diagnosed by experienced clinicians. Ultrasonic image will be reconstructed by artificial bee colony algorithm to improve its image display ability. The pathological diagnosis will be handed over to the physiological pathology laboratory of the hospital for diagnosis. The doctor's ultrasonic diagnosis results were compared with the pathological diagnosis stage results of patients, and the results were analyzed by statistical analysis to evaluate its diagnostic value. The comparison results showed that the number and classification of benign tumors were the same, while in malignant tumors, the number diagnosis was the same, but there was one patient with diagnostic error in classification. One case of mixed glial neuron tumor was diagnosed as glial neuron tumor, and the diagnostic accuracy was 94.44% and the

Indexed as

Artificial IntelligenceBrain NeoplasmsAlgorithmsFemaleHumansImage Processing, Computer-AssistedPregnancyUltrasonography

Identifiers

PMID34868516
PMCPMC8639249
OpenAlexW3217448044

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.