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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.
Fung, Russell; Villar, Jose; Dashti, Ali; Ismail, Leila Cheikh; Staines-Urias, Eleonora; Ohuma, Eric O; Salomon, Laurent J; Victora, Cesar G; Barros, Fernando C; Lambert, Ann; Carvalho, Maria; Jaffer, Yasmin A; Noble, J Alison; Gravett, Michael G; Purwar, Manorama; Pang, Ruyan; Bertino, Enrico; Munim, Shama; Min, Aung Myat; McGready, Rose; Norris, Shane A; Bhutta, Zulfiqar A; Kennedy, Stephen H; Papageorghiou, Aris T; Ourmazd, Abbas.
Afiliación
  • Fung R; Department of Physics, University of Wisconsin, Milwaukee, WI, USA.
  • Villar J; Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Dashti A; Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
  • Ismail LC; Department of Physics, University of Wisconsin, Milwaukee, WI, USA.
  • Staines-Urias E; Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Ohuma EO; College of Health Sciences, University of Sharjah, University City, United Arab Emirates.
  • Salomon LJ; Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Victora CG; Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Barros FC; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
  • Lambert A; Centre for Global Child Health, Hospital for Sick Children, Toronto, ON, Canada.
  • Carvalho M; Maternité Necker-Enfants Malades, Assistance publique - Hôpitaux de Paris (AP-HP), Université Paris Descartes, Paris, France.
  • Jaffer YA; Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Brazil.
  • Noble JA; Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, Brazil.
  • Gravett MG; Programa de Pós-Graduação em Saúde e Comportamento, Universidade Católica de Pelotas, Pelotas, Brazil.
  • Purwar M; Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
  • Pang R; Faculty of Health Sciences, Aga Khan University, Nairobi, Kenya.
  • Bertino E; Department of Family & Community Health, Ministry of Health, Muscat, Oman.
  • Munim S; Department of Engineering Science, University of Oxford, Oxford, UK.
  • Min AM; Department of Obstetrics and Gynecology, University of Washington, Seattle, WA, USA.
  • McGready R; Department of Global Health, University of Washington, Seattle, WA, USA.
  • Norris SA; Nagpur INTERGROWTH-21st Research Centre, Ketkar Hospital, Nagpur, India.
  • Bhutta ZA; School of Public Health, Peking University, Beijing, China.
  • Kennedy SH; Dipartimento di Scienze Pediatriche e dell' Adolescenza, Struttura Complessa Direzione Universitaria Neonatologia, Università di Torino, Torino, Italy.
  • Papageorghiou AT; Department of Obstetrics & Gynaecology, Division of Women & Child Health, Aga Khan University, Karachi, Pakistan.
  • Ourmazd A; Shoklo Malaria Research Unit (SMRU), Mahidol-Oxford Tropical Medicine Research Unit (MORU), Faculty of Tropical Medicine, Mahidol University, Mae Sot, Thailand.
Lancet Digit Health ; 2(7): e368-e375, 2020 07.
Article en En | MEDLINE | ID: mdl-32617525
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 2_ODS3 Problema de salud: 2_cobertura_universal / 2_salud_sexual_reprodutiva Asunto principal: Desarrollo Fetal / Exactitud de los Datos / Aprendizaje Automático Tipo de estudio: Clinical_trials / Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Pregnancy Idioma: En Revista: Lancet Digit Health Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 2_ODS3 Problema de salud: 2_cobertura_universal / 2_salud_sexual_reprodutiva Asunto principal: Desarrollo Fetal / Exactitud de los Datos / Aprendizaje Automático Tipo de estudio: Clinical_trials / Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Pregnancy Idioma: En Revista: Lancet Digit Health Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos