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"Interpretable machine learning model for predicting clinically significant ..."

Wenjun Zhao et al. (2024)

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DOI: 10.1186/S12880-024-01548-2

access: open

type: Journal Article

metadata version: 2025-01-07

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  dblp key:
  - journals/bmcmi/ZhaoHWSN24
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  persistent URL:
  - https://dblp.org/rec/journals/bmcmi/ZhaoHWSN24
Wenjun Zhao, Mengyan Hou, Juan Wang, Dan Song, Yongchao Niu:
Interpretable machine learning model for predicting clinically significant prostate cancer: integrating intratumoral and peritumoral radiomics with clinical and metabolic features. BMC Medical Imaging 24: 353 (2024)

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