ArticleBMC pregnancy and childbirth2025
CLP-Net: an advanced artificial intelligence technique for localizing standard planes of cleft lip and palate by three-dimensional ultrasound in the first trimester.
Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The intelligent lift: Artificial Intelligence's growing role in plastic surgery - a comprehensive review.Frontiers in surgery · 2025Pooled it
- From pixels to precision: a narrative review of AI-driven 3D morphological analysis and digital twinning in alveolar cleft management.Translational pediatrics · 2026Review
- Artificial intelligence applications in the diagnosis and management of cleft lip and palate: An updated review.Journal of dental sciences · 2026Review
- Application of an individualized nomogram in the first-trimester for predicting cleft lip and palate.BMC pregnancy and childbirth · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
Abstract
backgroundEarly diagnosis of cleft lip and palate (CLP) requires a multiplane examination, demanding high technical proficiency from radiologists. Therefore, this study aims to develop and validate the first artificial intelligence (AI)-based model (CLP-Net) for fully automated multi-plane localization in three-dimensional(3D) ultrasound during the first trimester.
methodsThis retrospective study included 418 (394 normal, 24 CLP) 3D ultrasound from 288 pregnant woman between July 2022 to October 2024 from Shenzhen Guangming District People's Hospital during the 11-13
resultsIn normal test set, mean angle(± SD)° and distance(± SD)mm differences were 6.24 ± 4.83, 9.81 ± 5.48, 15.36 ± 18.14 and 0.86 ± 0.72, 1.36 ± 1.15, 1.96 ± 2.35 for MSP ± SD, RTP ± SD and MAP ± SD, NCC and SSIM were 0.931 ± 0.079, 0.819 ± 0.122, 0.781 ± 0.157 and 0.896 ± 0.058, 0.785 ± 0.076, 0.726 ± 0.088 respectively. In the CLP cases, there were 8.61 ± 5.52, 10.67 ± 5.08, 16.91 ± 17.42 and 1.03 ± 1.20, 1.17 ± 1.08, 1.34 ± 0.95 for mean angle and distance in MSP, RTP, and MAP, respectively. NCC and SSIM were 0.876 ± 0.104, 0.803 ± 0.084, 0.793 ± 0.089 and 0.841 ± 0.105, 0.812 ± 0.085, 0.764 ± 0.100, respectively. CLP-Net predictions had a highly visual acceptance rate among radiologists (MSP: 95%, RTP: 70%, MAP: 70%), with improved localization speed 15s(31.3%) for senior radiologists and 63s(38.9%) for junior radiologists.
conclusionsCLP-Net accurately locates three planes for CLP screening, aiding radiologists and enhancing the efficiency of ultrasound examinations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.