Post-COVID-19 interstitial lung disease: Insights from a machine learning radiographic model

INTRODUCTION: Post-acute sequelae of COVID-19 seem to be an emerging global crisis. Machine learning radiographic models have great potential for meticulous evaluation of post-COVID-19 interstitial lung disease (ILD). METHODS: In this multicenter, retrospective study, we included consecutive patient...

Descripción completa

Detalles Bibliográficos
Autores principales: Karampitsakos, Theodoros, Sotiropoulou, Vasilina, Katsaras, Matthaios, Tsiri, Panagiota, Georgakopoulou, Vasiliki E., Papanikolaou, Ilias C., Bibaki, Eleni, Tomos, Ioannis, Lambiri, Irini, Papaioannou, Ourania, Zarkadi, Eirini, Antonakis, Emmanouil, Pandi, Aggeliki, Malakounidou, Elli, Sampsonas, Fotios, Makrodimitri, Sotiria, Chrysikos, Serafeim, Hillas, Georgios, Dimakou, Katerina, Tzanakis, Nikolaos, Sipsas, Nikolaos V., Antoniou, Katerina, Tzouvelekis, Argyris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886681/
https://www.ncbi.nlm.nih.gov/pubmed/36733935
http://dx.doi.org/10.3389/fmed.2022.1083264

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9886681/
https://www.ncbi.nlm.nih.gov/pubmed/36733935
http://dx.doi.org/10.3389/fmed.2022.1083264

Ejemplares similares