Evidence map›Paper›PMID 41301861›Full record

ArticleBiomedicines2025

Machine Learning-Based Prediction of IVF Outcomes: The Central Role of Female Preprocedural Factors.

Kristóf Bereczki, Mátyás Bukva, Viktor Vedelek, Bernadett Nádasdi, Zoltán Kozinszky, Rita Sinka, Csaba Bereczki, Anna Vágvölgyi, János Zádori

Abstract read
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In one paragraph

Article in Biomedicines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. 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

9 authors.

Kristóf BereczkiDepartment of Obstetrics and Gynecology, Albert Szent-Györgyi Medical School, University of Szeged, H-6725 Szeged, Hungary.
Mátyás BukvaDepartment of Immunology, Albert Szent-Györgyi Medical School, Faculty of Science and Informatics, University of Szeged, H-6720 Szeged, Hungary.
Viktor VedelekDepartment of Genetics, Faculty of Science and Informatics, University of Szeged, H-6726 Szeged, Hungary.ORCID 0000-0002-0420-8226
Bernadett NádasdiDepartment of Medicine, Albert Szent-Györgyi Medical School, University of Szeged, H-6725 Szeged, Hungary.
Zoltán KozinszkyDepartment of Obstetrics and Gynecology, Albert Szent-Györgyi Medical School, University of Szeged, H-6725 Szeged, Hungary.ORCID 0000-0001-7485-9895
Rita SinkaDepartment of Genetics, Faculty of Science and Informatics, University of Szeged, H-6726 Szeged, Hungary.ORCID 0000-0003-4040-4184
Csaba BereczkiDepartment of Pediatrics and Pediatric Health Center, University of Szeged Albert Szent-Györgyi Health Center, H-6725 Szeged, Hungary.
Anna VágvölgyiDepartment of Medicine, Albert Szent-Györgyi Medical School, University of Szeged, H-6725 Szeged, Hungary.ORCID 0000-0002-8810-700X
János ZádoriDepartment of Obstetrics and Gynecology, Albert Szent-Györgyi Medical School, University of Szeged, H-6725 Szeged, Hungary.ORCID 0000-0002-2560-2118

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

clinical pregnancyin vitro fertilizationlive birthmachine learningpreprocedural factors

Identifiers

PMID41301861
PMCPMC12649832

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.