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A machine learning framework develops a DNA replication stress model for predicting clinical outcomes and therapeutic vulnerability in primary prostate cancer

Crossref DOI link: https://doi.org/10.1186/s12967-023-03872-7

Published Online: 2023-01-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Huang, Rong-Hua

Hong, Ying-Kai

Du, Heng

Ke, Wei-Qi

Lin, Bing-Biao

Li, Ya-Lan https://orcid.org/0000-0002-3495-4721
Funding

Funding for this research was provided by:

Bethune Charitable Foundation (BCF-RF-WSQZTZJ-202011-061)
License Information

Text and Data Mining valid from 2023-01-12

Version of Record valid from 2023-01-12
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Article History

Received: 8 October 2022

Accepted: 2 January 2023

First Online: 12 January 2023

Declarations

:

: Not applicable.

: Not applicable.

: The authors declare no competing interests.

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