[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121641-en":3,"doc-seo-121641-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121641,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1784791008015729253",8,"Research & Report","Machine learning for accurate estimation of fetal gestational age based on ultrasound images - research study","Accurate gestational age estimation is essential for evidence-based obstetric care, yet last menstrual period dates are frequently unknown or uncertain. While early pregnancy ultrasound measurements are reliable, dating based on average fetal size becomes less accurate in the second and third trimesters, where biological variation and growth abnormalities widen error margins. This study applies state-of-the-art machine learning to estimate gestational age from standard ultrasound image analysis alone, using independent datasets for training/validation and external validation under blinded assessment of ground truth.","ARTICLE OPEN  \n[www.nature.com/npjdigitalmed](www.nature.com/npjdigitalmed)  \nMachine learning for accurate estimation of fetal gestational age based on ultrasound images  \nLok Hin Lee 1,19, Elizabeth Bradburn 2,19, Rachel Craik 2, Mohammad Yaqub3, Shane A. Norris4, Leila Cheikh Ismail5, Eric O. Ohuma2,6, Fernando C. Barros7,8, Ann Lambert2, Maria Carvalho9, Yasmin A. Jaffer10, Michael Gravett11, Manorama Purwar12, Qingqing Wu13, Enrico Bertino14, Shama Munim15, Aung Myat Min16, Zulfiqar Bhutta15,17, Jose Villar2,18, Stephen H. Kennedy2,18,  \nJ. Alison Noble 1,20 and Aris T. Papageorghiou 2,18,20 ✉  \n\n|  | Accurate estimation of gestational age is an essential component of good obstetric care and informs clinical decision-making throughout pregnancy. As the date of the last menstrual period is often unknown or uncertain, ultrasound measurement of fetal size is currently the best method for estimating gestational age. The calculation assumes an average fetal size at each gestational age. The method is accurate in the first trimester, but less so in the second and third trimesters as growth deviates from the average and variation in fetal size increases. Consequently, fetal ultrasound late in pregnancy has a wide margin of error of at least\u003Cbr>±2 weeks’ gestation. Here, we utilise state-of-the-art machine learning methods to estimate gestational age using only image analysis of standard ultrasound planes, without any measurement information. The machine learning model is based on ultrasound images from two independent datasets: one for training and internal validation, and another for external validation. During validation, the model was blinded to the ground truth of gestational age (based on a reliable last menstrual period date and confirmatory first-trimester fetal crown rump length) . We show that this approach compensates for increases in size variation and is even accurate in cases of intrauterine growth restriction. Our best machine-learning based model estimates gestational age with a mean absolute error of 3.0 (95% CI, 2.9–3.2) and 4.3 (95% CI, 4.1–4.5) days in the second and third trimesters, respectively, which outperforms current ultrasound-based clinical biometry at these gestational ages Our method for dating the pregnancy in the |  |\n| --- | --- | --- |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n|  |  |  |\n| .\u003Cbr>second and third trimesters is, therefore, more accurate than published methods. |  |  |\n|  | npj Digital Medicine (2023)6:36; [https://doi.org/10.1038/s41746-023-00774-2](https://doi.org/10.1038/s41746-023-00774-2) |  |\n|  |  |  |\n\nINTRODUCTION  \nFailure to estimate gestational age (GA) accurately remains an important barrier to the provision of evidence-based pregnancy care in many low- and middle-income countries (LMICs)1. An accurate estimate of GA is crucial to inform decision-making at the individual level. It is also essential at population level to measure causes of infant morbidity and mortality, such as preterm birth and small for GA (SGA)2 - information that is needed for public health strategies to improve health outcomes.  \nCurrently, ultrasound measurement of the fetal crown rump length (CRL) between 11 and 14 weeks’ gestation is the most accurate method to establish GA, i.e., the gold standard. However, many women, especially in LMICs, first seek antenatal care much later in pregnancy because of lack of resources and/or socio-cultural issues3,4. Relying on the reported last menstrual period (LMP) to estimate GA is invariably unhelpful due to inaccurate recall of dates, or irregular menstrual cycles, often exacerbated by malnutrition5.  \nConsequently, across the world, GA is mostly determined in the second and third trimesters by measurement of symphysis-fundal height (SFH) or fetal size using ultrasound. Even though ultrasound is more accurate than SFH measurement6, biometrybased GA assessment late in pregnancy is fun","cbCaice8BT5dzcLM","https://ap.wps.com/l/cbCaice8BT5dzcLM","pdf",2190299,1,11,"English","en",105,"# Introduction\n## Clinical need and limitations\n## Proposed machine learning approach","[{\"question\":\"Why is gestational age estimation difficult late in pregnancy?\",\"answer\":\"Ultrasound dating late in pregnancy assumes average fetal size, but fetal size variation increases and growth abnormalities become more common, widening prediction errors to at least about ±2 weeks.\"},{\"question\":\"How does the proposed method estimate gestational age?\",\"answer\":\"It uses machine learning models trained on standard ultrasound planes to estimate gestational age based only on image analysis, without using measurement inputs like fetal size measurements.\"},{\"question\":\"How was model performance validated?\",\"answer\":\"The model was trained and internally validated on one dataset and externally validated on a separate independent dataset, with validation blinded to gestational age ground truth derived from reliable last menstrual period and confirmatory early fetal crown-rump length.\"}]","Machine learning for accurate estimation of fetal gestational age based on ultrasound images - research study | PDF",1785805879,28,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"machine-learning-for-accurate-estimation-of-fetal-gestational-age-based-on-ultrasound-images-research-study","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/machine-learning-for-accurate-estimation-of-fetal-gestational-age-based-on-ultrasound-images-research-study/121641/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is gestational age estimation difficult late in pregnancy?","Question",{"text":75,"@type":76},"Ultrasound dating late in pregnancy assumes average fetal size, but fetal size variation increases and growth abnormalities become more common, widening prediction errors to at least about ±2 weeks.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the proposed method estimate gestational age?",{"text":80,"@type":76},"It uses machine learning models trained on standard ultrasound planes to estimate gestational age based only on image analysis, without using measurement inputs like fetal size measurements.",{"name":82,"@type":73,"acceptedAnswer":83},"How was model performance validated?",{"text":84,"@type":76},"The model was trained and internally validated on one dataset and externally validated on a separate independent dataset, with validation blinded to gestational age ground truth derived from reliable last menstrual period and confirmatory early fetal crown-rump length.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]