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Abstract
Accurate gestational age (GA) estimation is crucial for obstetric care. Ultrasound measurement of fetal size is the current best method, but accuracy decreases in later trimesters due to increased size variation. This study uses machine learning to estimate GA from ultrasound images without measurement information. The model, trained and validated on two independent datasets, achieves a mean absolute error of 3.0 and 4.3 days in the second and third trimesters respectively, outperforming current methods.
Publisher
npj Digital Medicine
Published On
Mar 09, 2023
Authors
Lok Hin Lee, Elizabeth Bradburn, Rachel Craik, Mohammad Yaqub, Shane A. Norris, Leila Cheikh Ismail, Eric O. Ohuma, Fernando C. Barros, Ann Lambert, Maria Carvalho, Yasmin A. Jaffer, Michael Gravett, Manorama Purwar, Qingqing Wu, Enrico Bertino, Shama Munim, Aung Myat Min, Zulfiqar Bhutta, Jose Villar, Stephen H. Kennedy, J. Alison Noble, Aris T. Papageorghiou
Tags
gestational age
ultrasound
machine learning
obstetric care
fetal size variation
accuracy
error

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