医学
胎龄
冠臀长度
超声波
妊娠期
产科
怀孕
放射科
孕早期
遗传学
生物
作者
Jeffrey S. A. Stringer,Teeranan Pokaprakarn,Juan Carlos Prieto,Bellington Vwalika,Srihari V Chari,Ntazana Sindano,Bethany L. Freeman,Bridget Sikapande,Nicole D. Armstrong,Yuri V. Sebastião,Nelly M. Mandona,Elizabeth M. Stringer,Chiraz BenAbdelkader,Mutinta Mungole,Filson M. Kapilya,Nariman Almnini,Arieska Nicole Diaz,Brittany A. Fecteau,Michael R. Kosorok,Stephen R. Cole,Margaret P. Kasaro
出处
期刊:JAMA
[American Medical Association]
日期:2024-08-01
卷期号:332 (8): 649-649
被引量:6
标识
DOI:10.1001/jama.2024.10770
摘要
Accurate assessment of gestational age (GA) is essential to good pregnancy care but often requires ultrasonography, which may not be available in low-resource settings. This study developed a deep learning artificial intelligence (AI) model to estimate GA from blind ultrasonography sweeps and incorporated it into the software of a low-cost, battery-powered device.
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