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引用本文的文献

1
A survey of obstetric ultrasound uses and priorities for artificial intelligence-assisted obstetric ultrasound in low- and middle-income countries.低收入和中等收入国家产科超声的使用情况及人工智能辅助产科超声的优先事项调查。
Sci Rep. 2025 Jan 31;15(1):3873. doi: 10.1038/s41598-025-87284-1.

本文引用的文献

1
Diagnostic Accuracy of an Integrated AI Tool to Estimate Gestational Age From Blind Ultrasound Sweeps.基于盲扫超声的集成 AI 工具估算胎龄的诊断准确性。
JAMA. 2024 Aug 27;332(8):649-657. doi: 10.1001/jama.2024.10770.
2
Artificial Intelligence in Obstetric Anomaly Scan: Heart and Brain.人工智能在产科超声异常扫描中的应用：心脏和脑部
Life (Basel). 2024 Jan 23;14(2):166. doi: 10.3390/life14020166.
3
Artificial intelligence assistance for fetal development: evaluation of an automated software for biometry measurements in the mid-trimester.人工智能辅助胎儿发育：中期妊娠自动软件生物测量评估。
BMC Pregnancy Childbirth. 2024 Feb 23;24(1):158. doi: 10.1186/s12884-024-06336-y.
4
Deep learning to estimate gestational age from fly-to cineloop videos: A novel approach to ultrasound quality control.深度学习从飞行动态循环视频估算胎龄：一种新的超声质量控制方法。
Int J Gynaecol Obstet. 2024 Jun;165(3):1013-1021. doi: 10.1002/ijgo.15321. Epub 2024 Jan 8.
5
Enhancing Fetal Anomaly Detection in Ultrasonography Images: A Review of Machine Learning-Based Approaches.增强超声图像中的胎儿异常检测：基于机器学习方法的综述
Biomimetics (Basel). 2023 Nov 2;8(7):519. doi: 10.3390/biomimetics8070519.
6
Deep learning for estimation of fetal weight throughout the pregnancy from fetal abdominal ultrasound.深度学习估计胎儿腹部超声整个孕期的体重。
Am J Obstet Gynecol MFM. 2023 Dec;5(12):101182. doi: 10.1016/j.ajogmf.2023.101182. Epub 2023 Oct 10.
7
Prediction Models for Intrauterine Growth Restriction Using Artificial Intelligence and Machine Learning: A Systematic Review and Meta-Analysis.使用人工智能和机器学习预测宫内生长受限的模型：系统评价与荟萃分析
Healthcare (Basel). 2023 Jun 1;11(11):1617. doi: 10.3390/healthcare11111617.
8
Machine learning applied in maternal and fetal health: a narrative review focused on pregnancy diseases and complications.机器学习在母婴健康中的应用：一篇以妊娠疾病和并发症为重点的叙述性综述。
Front Endocrinol (Lausanne). 2023 May 19;14:1130139. doi: 10.3389/fendo.2023.1130139. eCollection 2023.
9
AI Estimation of Gestational Age from Blind Ultrasound Sweeps in Low-Resource Settings.在资源匮乏地区通过盲法超声扫描进行人工智能估算孕周
NEJM Evid. 2022 May;1(5). doi: 10.1056/evidoa2100058. Epub 2022 Mar 28.
10
How to improve access to medical imaging in low- and middle-income countries ?如何改善低收入和中等收入国家获取医学影像的状况？
EClinicalMedicine. 2021 Jul 17;38:101034. doi: 10.1016/j.eclinm.2021.101034. eCollection 2021 Aug.

Enhancing Obstetric Ultrasonography With Artificial Intelligence in Resource-Limited Settings.

作者信息

Gimovsky Alexis C, Eke Ahizechukwu C, Tuuli Methodius G

机构信息

Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Women & Infants Hospital of Rhode Island, Alpert Medical School of Brown University, Providence, Rhode Island.

Division of Maternal-Fetal Medicine, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, Maryland.

出版信息

JAMA. 2024 Aug 27;332(8):626-628. doi: 10.1001/jama.2024.14794.

DOI:10.1001/jama.2024.14794
PMID:39088222
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11863673/
Abstract
摘要