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Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images
Noninvasive, radiological image-based detection and stratification of Gleason patterns can impact clinical outcomes, treatment selection, and the determination of disease status at diagnosis without subjecting patients to surgical biopsies. We present machine learning-based automatic classification...
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| Vydáno v: | Proc Natl Acad Sci U S A |
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| Hlavní autoři: | , , , , , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
National Academy of Sciences
2015
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4655555/ https://ncbi.nlm.nih.gov/pubmed/26578786 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1505935112 |
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