Cargando…
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...
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: | |
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 |
Ejemplares similares
-
The Metabolic Reprogramming of Frem2 Mutant Mice Embryos in Cryptophthalmos Development
por: Zhang, Xiayin, et al.
Publicado: (2021) -
Automatic identification of myopia based on ocular appearance images using deep learning
por: Yang, Yahan, et al.
Publicado: (2020) -
Artificial intelligence deciphers codes for color and odor perceptions based on large-scale chemoinformatic data
por: Zhang, Xiayin, et al.
Publicado: (2020) -
The combination of brain-computer interfaces and artificial intelligence: applications and challenges
por: Zhang, Xiayin, et al.
Publicado: (2020) -
Attitudes towards medical artificial intelligence talent cultivation: an online survey study
por: Yun, Dongyuan, et al.
Publicado: (2020)