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CBCT radiomic features-based machine learning prediction models and nomogram for treatment decision-making regarding surgery-first approach in skeletal Class III malocclusion

Crossref DOI link: https://doi.org/10.1186/s12903-025-06702-y

Published Online: 2025-09-26

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

Authors

Bao, Yingzhu

Qi, Keying

Yang, Le

Chen, Yufan

Zhou, Chen

Wang, Weicai

Bao, Baicheng

Long, Xiaojing

Zheng, Guangsen

Wang, Xi
Funding

Funding for this research was provided by:

IOF Young Research Grant (IOF2023Y09)

National Natural Science Foundation of China (82201060)
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Text and Data Mining valid from 2025-09-26

Version of Record valid from 2025-09-26
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Article History

Received: 4 April 2025

Accepted: 25 July 2025

First Online: 26 September 2025

Declarations

:

: This study was approved by the Ethics Committee of Hospital of Stomatology, Sun Yat-sen University, with a reference number of (GHKQ-202401-L2), and the conduct of the study adheres to the Declaration of Helsinki and relevant ethical standards. Informed consent was obtained from all participants prior to their involvement in the study. Clinical trial number is not applicable.

: Not applicable.

: The authors declare no competing interests.

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