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Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>We developed a deep learning model trained on over two million ultrasound images from 78,531 pregnancies from Australia, India, and the UK to estimate gestational age (GA) directly from any fetal ultrasound image, regardless of orientation. The model outputs both a GA estimate and an uncertainty value based on image quality. Independent validation on 36,762 ultrasound images from 742 fetuses showed a mean absolute error (MAE) of 1.7 days at 14\u201318 weeks and 2.8 days at 18\u201324 weeks, significantly outperforming traditional biometry (p\u2009&lt;\u20090.001). In video analysis, the model achieved a median prediction time of 24\u2009s and an MAE below 3 days across all trimesters. Performance was consistent across maternal body mass index (BMI) categories and geographic settings. 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