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Titre: | Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countries |
Auteur(s): | Sendra-Balcells, Carla Campello, Víctor M. Torrents-Barrena, Jordina Ammar, Mohammed |
Date de publication: | 2023 |
Editeur: | Nature Research |
Collection/Numéro: | Scientific Reports/ Vol.13, N°1 (2023);p.1 |
Résumé: | The Funding section in the original version of this Article was incomplete. “This work received funding from the European Union’s 2020 research and innovation programme under Grant Agreement No. 825903 (euCanSHare project), as well as from the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-099898-B-I00. Additionally, the research leading to these results has received funding from Cerebra Foundation for the Brain Injured Child (Carmarthen, Wales, UK).” now reads: “This work received funding from the European Union’s 2020 research and innovation programme under Grant Agreement No. 825903 (euCanSHare project), as well as from the Spanish Ministry of Science, Innovation and Universities under grant agreement RTI2018-099898-B-I00. Additionally, the research leading to these results has received funding from Cerebra Foundation for the Brain Injured Child (Carmarthen, Wales, UK). This research was partly funded by a grant from the European Research Council (ERC) under the European Union’s Horizon Europe research and innovation programme (AIMIX project - grant agreement No. 101044779).” |
URI/URL: | https://doi.org/10.1038/s41598-023-29490-3 https://www.nature.com/articles/s41598-023-30540-z http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/11182 |
ISSN: | 20452322 |
Collection(s) : | Publications Internationales
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