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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

Autor: 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, S Norris, SE Abbott, A Abubakar, J Acedo, I Ahmed, F Al-Aamri, J Al-Abduwani, J Al-Abri, D Alam, E Albernaz, H Algren, F Al-Habsi, M Alija, H Al-Jabri, H Al-Lawatiya, B Al-Rashidiya, DG Altman, WK Al-Zadjali, HF Andersen, L Aranzeta, S Ash, M Baricco, FC Barros, H Barsosio, C Batiuk, M Batra, J Berkley, E Bertino, MK Bhan, BA Bhat, ZA Bhutta, I Blakey, S Bornemeier, A Bradman, M Buckle, O Burnham, F Burton, A Capp, VI Cararra, R Carew, VI Carrara, AA Carter, M Carvalho, P Chamberlain, Ismail L Cheikh, L Cheikh Ismail, A Choudhary, S Choudhary, WC Chumlea, C Condon, LA Corra, C Cosgrove, R Craik, MF da Silveira, D Danelon, T de Wet, E de Leon, S Deshmukh, G Deutsch, J Dhami, Nicola P Di, M Dighe, H Dolk, M Domingues, D Dongaonkar, D Enquobahrie, B Eskenazi, F Farhi, M Fernandes, D Finkton, S Fonseca, IO Frederick, M Frigerio, P Gaglioti, C Garza, G Gilli, P Gilli, M Giolito, F Giuliani, J Golding, MG Gravett, SH Gu, Y Guman, YP He, L Hoch, S Hussein, D Ibanez, C Ioannou, N Jacinta, N Jackson, YA Jaffer, S Jaiswal, JM Jimenez-Bustos, FR Juangco, L Juodvirsiene, M Katz, B Kemp, S Kennedy, M Ketkar, V Khedikar, M Kihara, J Kilonzo, C Kisiang'ani, J Kizidio, CL Knight, HE Knight, N Kunnawar, A Laister, A Lambert, A Langer, T Lephoto, A Leston, T Lewis, H Liu, S Lloyd, P Lumbiganon, S Macauley, E Maggiora, C Mahorkar, M Mainwaring, L Malgas, A Matijasevich, K McCormick, R McGready, R Miller, A Min, A Mitidieri, V Mkrtychyan, B Monyepote, D Mota, I Mulik, S Munim, D Muninzwa, N Musee, S Mwakio, H Mwangudzah, R Napolitano, CR Newton, V Ngami, JA Noble, T Norris, F Nosten, K Oas, M Oberto, L Occhi, R Ochieng, EO Ohuma, E Olearo, I Olivera, MG Owende, C Pace, Y Pan, RY Pang, AT Papageorghiou, B Patel, V Paul, W Paulsene, F Puglia, M Purwar, V Rajan, A Raza, D Reade, J Rivera, DA Rocco, F Roseman, S Roseman, C Rossi, PM Rothwell, I Rovelli, K Saboo, R Salam, M Salim, L Salomon, Luna M Sanchez, J Sande, I Sarris, S Savini, IK Sclowitz, A Seale, J Shah, M Sharps, C Shembekar, YJ Shen, M Shorten, F Signorile, A Singh, S Sohoni, A Somani, TK Sorensen, A Soria- Frisch, E Staines Urias, A Stein, W Stones, V Taori, K Tayade, T Todros, R Uauy, A Varalda, M Venkataraman, C Victora, J Villar, S Vinayak, S Waller, L Walusuna, JH Wang, L Wang, S Wanyonyi, D Weatherall, S Wiladphaingern, A Wilkinson, D Wilson, MH Wu, QQ Wu, K Wulff, D Yellappan, Y Yuan, S Zaidi, G Zainab, JJ Zhang, Y Zhang

Publikováno v: The Lancet. Digital Health

Summary Background Preterm birth is a major global health challenge, the leading cause of death in children under 5 years of age, and a key measure of a population's general health and nutritional status. Current clinical methods of estimating fetal

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b00cec389c2bca87ad736139f7a036ce
https://ora.ox.ac.uk/objects/uuid:cbd19118-0020-4e51-87e3-c0d0560a121f

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