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Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study: a population-based machine learning study

  • for the International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st)
  • , Russell Fung
  • , Jose Villar
  • , Ali Dashti
  • , Leila Cheikh Ismail
  • , Eleonora Staines-Urias
  • , Eric O. Ohuma
  • , Laurent J. Salomon
  • , Cesar G. Victora
  • , Fernando C. Barros
  • , Ann Lambert
  • , Maria Carvalho
  • , Yasmin A. Jaffer
  • , J. Alison Noble
  • , Michael G. Gravett
  • , Manorama Purwar
  • , Ruyan Pang
  • , Enrico Bertino
  • , Shama Munim
  • , Aung Myat Min
    • Rose McGready, Shane A. Norris, Zulfiqar A. Bhutta, Stephen H. Kennedy, Aris T. Papageorghiou, Abbas Ourmazd
  • University of Wisconsin-Milwaukee
  • University of Oxford
  • University of Sharjah
  • University of Toronto
  • Université Paris Cité
  • Universidade Federal de Pelotas
  • Aga Khan University
  • Ministry of Health, Oman
  • University of Washington
  • Ketkar Hospital
  • Peking University
  • University of Turin
  • Mahidol University
  • University of the Witwatersrand
  • Liverpool School of Tropical Medicine, Liverpool, UK

Research output: Contribution to journal › Article › peer-review

70 Citations (Scopus)

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