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Artificial intelligence algorithm for preoperative prediction of FIGO stage in ovarian cancer based on clinical features integrated 18F-FDG PET/CT metabolic and radiomics features

Crossref DOI link: https://doi.org/10.1007/s00432-025-06134-9

Published Online: 2025-02-20

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

Authors

Xu, Shilin

Zhu, Chengguang

Wu, Meixuan

Gu, Sijia

Wu, Yongsong

Cheng, Shanshan

Wang, Chao

Zhang, Yue

Zhang, Weixia

Shen, Wei

Yang, Jiani

Yang, Xiaokang

Wang, Yu
Funding

Funding for this research was provided by:

Shanghai Municipal Science and Technology Major Project (2021SHZDZX0102, 2021SHZDZX0102, 2021SHZDZX0102)

National Natural Science Foundation of China (82102856, 82102856)

the Fundamental Research Funds for the Central Universities, the National Key R&D Program of China (2022YFF1202600, 2022YFF1202600)

Science and Technology Commission of Shanghai Municipality (23YF1433600)
License Information

Text and Data Mining valid from 2025-02-20

Version of Record valid from 2025-02-20
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Article History

Received: 4 June 2024

Accepted: 4 February 2025

First Online: 20 February 2025

Declarations

:

: The authors declare no competing interests.

: The local ethics committee approved the study protocol and informed consent was obtained from all individual participants included in the study.

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