Unsupervised machine learning for identifying important visual features through bag-of-words using histopathology data from chronic kidney disease

Pathologists use visual classification to assess patient kidney biopsy samples when diagnosing the underlying cause of kidney disease. However, the assessment is qualitative, or semi-quantitative at best, and reproducibility is challenging. To discover previously unknown features which predict patie...

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Detalles Bibliográficos
Autores principales: Lee, Joonsang, Warner, Elisa, Shaikhouni, Salma, Bitzer, Markus, Kretzler, Matthias, Gipson, Debbie, Pennathur, Subramaniam, Bellovich, Keith, Bhat, Zeenat, Gadegbeku, Crystal, Massengill, Susan, Perumal, Kalyani, Saha, Jharna, Yang, Yingbao, Luo, Jinghui, Zhang, Xin, Mariani, Laura, Hodgin, Jeffrey B., Rao, Arvind
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8941143/
https://www.ncbi.nlm.nih.gov/pubmed/35318420
http://dx.doi.org/10.1038/s41598-022-08974-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8941143/
https://www.ncbi.nlm.nih.gov/pubmed/35318420
http://dx.doi.org/10.1038/s41598-022-08974-8

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