ReviewFrontiers in medicine2021
Artificial Intelligence in Prenatal Ultrasound Diagnosis.
Review in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06952439 (Prospective Multicenter Study to Evaluate the Performance of the Artificial Intelligence), which is not on this map. Cited by 18 papers, 4 of them syntheses 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.
Prospective Multicenter Study to Evaluate the Performance of the Artificial Intelligence (AI)/ Machine Learning (ML) Technologies Utilized by the Origin Medical EXAM ASSISTANT
Who cites it
18 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Congenital heart disease diagnosis using machine learning: a systematic literature review.Frontiers in medicine · 2026Pooled it
- Precision medicine exploration of postpartum rectus abdominis muscle separation: from basic research to clinical practice.BMC surgery · 2025Pooled it
- Diagnostic accuracy of artificial intelligence models in detecting congenital heart disease in the second-trimester fetus through prenatal cardiac screening: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2025Pooled it
- Applications of artificial intelligence in early childhood health management: a systematic review from fetal to pediatric periods.Frontiers in pediatrics · 2025Pooled it
- Review
- Optimized fetal head circumference estimation in 2D ultrasound using EfficientNet-B7 and Adam optimizer.BMC pediatrics · 2026Article
- Quality evaluation of ultrasound images for fetal crown-rump length measurement at 11 to 14 weeks' gestation: A fusion model can be interpreted using SHAP method.The ultrasound journal · 2026Article
- AI-based quality control was associated with improved fetal ultrasound image quality in low-resource settings: a real-world multicenter study from West China.BMC medicine · 2026Observational
- Intelligent quality control for first trimester ultrasound scans in Liaoning Province of China.NPJ digital medicine · 2025Article
- Automatic Identification of Fetal Abdominal Planes from Ultrasound Images Based on Deep Learning.Journal of imaging informatics in medicine · 2025Article
- Artificial intelligence-based prenatal ultrasound for diagnosing fetal lip and palate during the second trimester.Quantitative imaging in medicine and surgery · 2025Article
- Detecting microcephaly and macrocephaly from ultrasound images using artificial intelligence.BMC medical imaging · 2025Article
- Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.Scientific reports · 2025Article
- Research advancements in the Use of artificial intelligence for prenatal diagnosis of neural tube defects.Frontiers in pediatrics · 2025Review
- Repeatability and reproducibility of artificial intelligence-acquired fetal brain measurements (SonoCNS) in the second and third trimesters of pregnancy.Scientific reports · 2024Article
- Observational
- A Deep-Learning-Based Method Can Detect Both Common and Rare Genetic Disorders in Fetal Ultrasound.Biomedicines · 2023Article
- Application and Progress of Artificial Intelligence in Fetal Ultrasound.Journal of clinical medicine · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of artificial intelligence (AI) technology to medical imaging has resulted in great breakthroughs. Given the unique position of ultrasound (US) in prenatal screening, the research on AI in prenatal US has practical significance with its application to prenatal US diagnosis improving work efficiency, providing quantitative assessments, standardizing measurements, improving diagnostic accuracy, and automating image quality control. This review provides an overview of recent studies that have applied AI technology to prenatal US diagnosis and explains the challenges encountered in these applications.
Indexed as
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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.