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Scientific article
English

Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning

Published inLa Radiologia Medica, vol. 125, no. 8, p. 754-762
Publication date2020
Abstract

To identify optimal classification methods for computed tomography (CT) radiomics-based preoperative prediction of clear cell renal cell carcinoma (ccRCC) grade.

Keywords
  • Computed tomography (CT)
  • Fuhrman grading
  • Machine learning
  • Radiomics
  • Renal cell carcinoma
Citation (ISO format)
NAZARI, Mostafa et al. Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning. In: La Radiologia Medica, 2020, vol. 125, n° 8, p. 754–762. doi: 10.1007/s11547-020-01169-z
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Article (Published version)
accessLevelRestricted
Identifiers
ISSN of the journal1826-6983
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Technical informations

Creation04/29/2020 4:15:00 PM
First validation04/29/2020 4:15:00 PM
Update time03/15/2023 10:05:04 PM
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