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CT imaging-based machine learning model: a potential modality for predicting low-risk and high-risk groups of thymoma: “Impact of surgical modality choice”

Crossref DOI link: https://doi.org/10.1186/s12957-021-02259-6

Published Online: 2021-05-11

Published Print: 2021-12

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

Authors

Kayi Cangir, Ayten https://orcid.org/0000-0002-2052-1642
Orhan, Kaan

Kahya, Yusuf

Özakıncı, Hilal

Kazak, Betül Bahar

Konuk Balcı, Buse Mine

Karasoy, Duru

Uzun, Çağlar
License Information

Text and Data Mining valid from 2021-05-11

Version of Record valid from 2021-05-11
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Article History

Received: 28 December 2020

Accepted: 4 May 2021

First Online: 11 May 2021

Declarations

:

: All procedures performed in studies involving human participants were in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards. For this type of study, ethical committee approval and formal consent is not required. Informed consent was obtained from all individual participants included in the study.

: Not applicable

: The authors declare that they have no competing interests.

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