Human embryonic stem cell classification: random network with autoencoded feature extractor

Significance: Automated understanding of human embryonic stem cell (hESC) videos is essential for the quantified analysis and classification of various states of hESCs and their health for diverse applications in regenerative medicine. Aim: This paper aims to develop an ensemble method and bagging o...

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Detalles Bibliográficos
Autores principales: Guan, Benjamin X., Bhanu, Bir, Theagarajan, Rajkumar, Liu, Hengyue, Talbot, Prue, Weng, Nikki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2021
Materias:
Special Series on Artificial Intelligence and Machine Learning in Biomedical Optics
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084167/
https://www.ncbi.nlm.nih.gov/pubmed/33928769
http://dx.doi.org/10.1117/1.JBO.26.5.052913

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8084167/
https://www.ncbi.nlm.nih.gov/pubmed/33928769
http://dx.doi.org/10.1117/1.JBO.26.5.052913

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