Evidence map›Paper›PMID 41007621›Full record

ArticleBiomedicines2025

Machine Learning Prediction of Short Cervix in Mid-Pregnancy Based on Multimodal Data from the First-Trimester Screening Period: An Observational Study in a High-Risk Population.

Shengyu Wu, Jiaqi Dong, Jifan Shi, Xiaoxian Qu, Yirong Bao, Xiaoyuan Mao, Mu Lv, Xuan Chen, Hao Ying

Abstract read
PubMed Full text at PMC Publisher
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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Shengyu WuDepartment of Obstetrics, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai 200092, China.
Jiaqi DongDepartment of Obstetrics, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai 200092, China.
Jifan ShiResearch Institute of Intelligent Complex Systems, Fudan University, Shanghai 200433, China.ORCID 0000-0002-2471-0686
Xiaoxian QuDepartment of Obstetrics, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai 200092, China.
Yirong BaoDepartment of Obstetrics, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai 200092, China.
Xiaoyuan MaoDepartment of Obstetrics, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai 200092, China.
Mu LvDepartment of Obstetrics, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai 200092, China.
Xuan ChenDepartment of Obstetrics, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai 200092, China.
Hao YingDepartment of Obstetrics, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University; Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai 200092, China.ORCID 0000-0002-6098-7017

Funding

Key Research Project of Pudong New Area Population and Family Planning Commission PW2020E-1National Key Research and Development Program 2022YFC2704600National Key Research and Development Program 2022YFC2704604National Natural Science Foundation of China 82071678National Natural Science Foundation of China 82271719Program of Shanghai Academic/Technology Research Leader 23XD1402700Shanghai Municipal Science and Technology Commission Research Fund 21140903800
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

machine learningmid-pregnancyprediction modelpreterm birthshort cervix

Identifiers

PMID41007621
PMCPMC12467863

What Socratic 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 Socratic graph.