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Radiomic Features and Machine Learning for the Discrimination of Renal Tumor Histological Subtypes: A Pragmatic Study Using Clinical-Routine Computed Tomography
SIMPLE SUMMARY: This study evaluates how advanced image analyses (radiomic features) and machine learning algorithms can help to distinguish subtypes of kidney tumors in computed tomography (CT) images, which is important for further patient treatment. For 201 patients, the image analyses showed a m...
Gespeichert in:
| Veröffentlicht in: | Cancers (Basel) |
|---|---|
| Hauptverfasser: | , , , , , , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
MDPI
2020
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7603020/ https://ncbi.nlm.nih.gov/pubmed/33081400 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/cancers12103010 |
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