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AI-driven 3D virtual surgical planning in total hip arthroplasty: a machine learning approach for precision implant positioning and improved clinical outcomes

Crossref DOI link: https://doi.org/10.1186/s13018-026-06727-1

Published Online: 2026-02-07

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

Authors

Xi, Li-Cheng

Yang, Bang-qi

Jiang, Lin-Hua

Xu, You-gao

Shen, Chong
Funding

Funding for this research was provided by:

Innovation Project of Guangxi Graduate Education (no. YCBZ2025198)
License Information

Text and Data Mining valid from 2026-02-07

Version of Record valid from 2026-03-11
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Article History

Received: 26 October 2025

Accepted: 25 January 2026

First Online: 7 February 2026

Declarations

:

: Ethical approval was obtained from Institutional Review Board of the Liuzhou Workers’ Hospital (J2023027), and this study had been performed in accordance with the ethical standards in the 1964 Declaration of Helsinki.Informed consent: Informed consent was obtained from all patients included in the study.

: All authors have read and approved the content, and agree to submit it for consideration for publication.

: The authors declare no competing interests.

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