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Use of radiomics based on 18F-FDG PET/CT and machine learning methods to aid clinical decision-making in the classification of solitary pulmonary lesions: an innovative approach

Crossref DOI link: https://doi.org/10.1007/s00259-021-05220-7

Published Online: 2021-02-05

Published Print: 2021-08

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

Authors

Zhou, Yi

Ma, Xue-lei

Zhang, Ting

Wang, Jian

Zhang, Tao

Tian, Rong https://orcid.org/0000-0002-5191-9004
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (81971653)

Ministry of Science and Technology (2019YFS0373)
License Information

Text and Data Mining valid from 2021-02-05

Version of Record valid from 2021-02-05
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Article History

Received: 20 September 2020

Accepted: 25 January 2021

First Online: 5 February 2021

Compliance with ethical standards

:

: All authors declare no conflicts of interest.

: The clinical institutional review board approved this study.

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