Cargando…
A deep convolutional neural network for classification of red blood cells in sickle cell anemia
Sickle cell disease (SCD) is a hematological disorder leading to blood vessel occlusion accompanied by painful episodes and even death. Red blood cells (RBCs) of SCD patients have diverse shapes that reveal important biomechanical and bio-rheological characteristics, e.g. their density, fragility, a...
Autores principales: | Xu, Mengjia, Papageorgiou, Dimitrios P., Abidi, Sabia Z., Dao, Ming, Zhao, Hong, Karniadakis, George Em |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5654260/ https://www.ncbi.nlm.nih.gov/pubmed/29049291 http://dx.doi.org/10.1371/journal.pcbi.1005746 |
Ejemplares similares
-
Simultaneous polymerization and adhesion under hypoxia in sickle cell disease
por: Papageorgiou, Dimitrios P., et al.
Publicado: (2018) -
Quantifying Fibrinogen-Dependent Aggregation of Red Blood Cells in Type 2 Diabetes Mellitus
por: Deng, Yixiang, et al.
Publicado: (2020) -
Classification of red cell dynamics with convolutional and recurrent neural networks: a sickle cell disease case study
por: Darrin, Maxime, et al.
Publicado: (2023) -
Patient-specific modeling of individual sickle cell behavior under transient hypoxia
por: Li, Xuejin, et al.
Publicado: (2017) -
Quantitative prediction of erythrocyte sickling for the development of advanced sickle cell therapies
por: Lu, Lu, et al.
Publicado: (2019)