Evidence map›Paper›PMID 34524706›Full record

ReviewJournal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine2022

Artificial Intelligence in the Assessment of Female Reproductive Function Using Ultrasound: A Review.

Zhiyi Chen, Ziyao Wang, Meng Du, Zhenyu Liu

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 8% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Multimodal ultrasound assessment of ovarian reserve.Abdominal radiology (New York) · 2026
    Review
  4. Article
  5. Radiomics and radiogenomics in ovarian cancer: a review with a focus on ultrasound applications.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Review
  6. Drug and therapeutic intravaginal delivery targeting diseases in the female reproductive tract: A mathematical modeling perspective.Journal of controlled release : official journal of the Controlled Release Society · 2025
    Review
  7. Review
  8. Review
  9. Review
  10. Article
  11. In Contemporary Reproductive Medicine Human Beings are Not Yet Dispensable.Journal of obstetrics and gynaecology of India · 2023
    Article
  12. Review
  13. Article
  14. Review
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Zhiyi ChenThe First Affiliated Hospital, Medical Imaging Center, Hengyang Medical School, University of South China, Hengyang, China.
Ziyao WangThe First Affiliated Hospital, Medical Imaging Center, Hengyang Medical School, University of South China, Hengyang, China.
Meng DuInstitute of Medical Imaging, University of South China, Hengyang, China.
Zhenyu LiuThe First Affiliated Hospital, Medical Imaging Center, Hengyang Medical School, University of South China, Hengyang, China.
University of South China · CN

Funding

Clinical Research 4310 Program of the First Affiliated Hospital of The University of South China 4310-2021-K06National Key R&D Program of China 2019YFE0110400
6 · The paper itself

Abstract

The incidence of infertility is continuously increasing nearly all over the world in recent years, and novel methods for accurate assessment are of great need. Artificial Intelligence (AI) has gradually become an effective supplementary method for the assessment of female reproductive function. It has been used in clinical follicular monitoring, optimum timing for transplantation, and prediction of pregnancy outcome. Some literatures summarize the use of AI in this field, but few of them focus on the assessment of female reproductive function by AI-aided ultrasound. In this review, we mainly discussed the applicability, feasibility, and value of clinical application of AI in ultrasound to monitor follicles, assess endometrial receptivity, and predict the pregnancy outcome of in vitro fertilization and embryo transfer (IVF-ET). The limitations, challenges, and future trends of ultrasound combined with AI in providing efficient and individualized evaluation of female reproductive function had also been mentioned.

Indexed as

Artificial IntelligenceInfertilityEmbryo TransferEndometriumFemaleFertilization in VitroHumansPregnancyartificial intelligenceendometrial receptivityinfertilityovarian responseultrasound

Identifiers

PMID34524706
PMCPMC9292970
OpenAlexW3201342980

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.