Advancing precision single-cell analysis of red blood cells through semi-supervised deep learning using database of patients with post-COVID-19 syndrome-Reference-Cited by-同舟云学术

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Advancing precision single-cell analysis of red blood cells through semi-supervised deep learning using database of patients with post-COVID-19 syndrome

Published:2024-03-12 Issue: Volume:109 Page:5
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Container-title:Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XXII
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Author:

Kurenkov Andrey,Kussanova Aigul,Barteneva Natasha S.

Publisher

SPIE

Reference44 articles.

1. Imaging Flow Cytometry

2. Cellular Heterogeneity

3. Emerging properties in self-supervised vision transformers;Caron,2021

4. Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Systematic review and meta-analysis of cryopreserved bovine sperm assessment: harnessing imaging flow cytometry for multi-parametric analysis;Frontiers in Veterinary Science;2024-04-24

2. Deformability of Heterogeneous Red Blood Cells in Aging and Related Pathologies;Aging and disease;2024

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