Evidence map›Paper›PMID 40182169›Full record

ReviewCureus2025

Artificial Intelligence in Assisted Reproductive Technology: A New Era in Fertility Treatment.

Eirini Orovou, Katerina D Tzimourta, Maria Tzitiridou-Chatzopoulou, Antigoni Kakatosi, Antigoni Sarantaki

Abstract readReview
In one paragraph

Review in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
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

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Genetic and Epigenetic Risks of Male Infertility in ART.International journal of molecular sciences · 2025
    Review
  9. Review
  10. Review
  11. 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

5 authors.

Eirini OrovouDepartment of Midwifery, University of Western Macedonia, Ptolemaida, GRC.
Katerina D TzimourtaDepartment of Electrical and Computer Engineering, University of Western Macedonia, Kozani, GRC.
Maria Tzitiridou-ChatzopoulouDepartment of Midwifery, University of Western Macedonia, Ptolemaida, GRC.
Antigoni KakatosiDepartment of Electrical and Computer Engineering, University of Western Macedonia, Kozani, GRC.
Antigoni SarantakiDepartment of Midwifery, University of West Attica, Athens, GRC.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) is increasingly applied in assisted reproduction, enhancing success rates and enabling personalized fertility care. The theoretical background of this paper seeks to present an extensive analysis of the key concepts, technological developments, and applications of AI in the field of assisted reproduction. Through a review of existing literature, clinical studies, and practical applications, this paper attempts to demonstrate how AI can contribute to increasing the effectiveness of fertility treatments, address ethical and legal issues, and open new avenues for research and clinical practice in the future.

Indexed as

artificial intelligence (ai)assisted reproductive technology (art)decision support systemdeep learningin vitro fertilization (ivf)machine learning (ml)reproductive medicine

Identifiers

PMID40182169
PMCPMC11966177

What OpenQuestion holds

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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.