Automated analysis of high‐content microscopy data with deep learning

Existing computational pipelines for quantitative analysis of high‐content microscopy data rely on traditional machine learning approaches that fail to accurately classify more than a single dataset without substantial tuning and training, requiring extensive analysis. Here, we demonstrate that the...

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Detalles Bibliográficos
Autores principales: Kraus, Oren Z, Grys, Ben T, Ba, Jimmy, Chong, Yolanda, Frey, Brendan J, Boone, Charles, Andrews, Brenda J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408780/
https://www.ncbi.nlm.nih.gov/pubmed/28420678
http://dx.doi.org/10.15252/msb.20177551

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5408780/
https://www.ncbi.nlm.nih.gov/pubmed/28420678
http://dx.doi.org/10.15252/msb.20177551

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