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Glioma Grading via Analysis of Digital Pathology Images Using Machine Learning
Cancer pathology reflects disease progression (or regression) and associated molecular characteristics, and provides rich phenotypic information that is predictive of cancer grade and has potential implications in treatment planning and prognosis. According to the remarkable performance of computati...
Autores principales: | Rathore, Saima, Niazi, Tamim, Iftikhar, Muhammad Aksam, Chaddad, Ahmad |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7139732/ https://www.ncbi.nlm.nih.gov/pubmed/32131409 http://dx.doi.org/10.3390/cancers12030578 |
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