An artificial intelligent platform for live cell identification and the detection of cross-contamination

BACKGROUND: About 30% of cell lines have been cellular cross-contaminated and misidentification, which can result in invalidated experimental results and unusable therapeutic products. Cell morphology under the microscope was observed routinely, and further DNA sequencing analysis was performed peri...

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Detalles Bibliográficos
Autores principales: Wang, Ruixin, Wang, Dongni, Kang, Dekai, Guo, Xusen, Guo, Chong, Dongye, Meimei, Zhu, Yi, Chen, Chuan, Zhang, Xiayin, Long, Erping, Wu, Xiaohang, Liu, Zhenzhen, Lin, Duoru, Wang, Jinghui, Huang, Kai, Lin, Haotian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Original Article on Medical Artificial Intelligent Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327366/
https://www.ncbi.nlm.nih.gov/pubmed/32617317
http://dx.doi.org/10.21037/atm.2019.07.105

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327366/
https://www.ncbi.nlm.nih.gov/pubmed/32617317
http://dx.doi.org/10.21037/atm.2019.07.105

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