Patient-specific musculoskeletal modeling to enhance preoperative planning for pelvic fracture reduction
Our method transforms pelvic fracture management by translating surgical expertise into quantifiable, data-rich biomechanical parameters. This data-driven framework not only enables optimized surgical planning for both robotic and manual procedures but also provides a high-resolution quantitative basis for AI-enhanced decision support. By shifting the field from a subjective art to an objective science, our approach standardizes surgical outcomes and paves the way for intelligent systems that deliver more precise and higher-quality surgical planning.
Authors
- Sutuke Yibulayimu (ORCID: https://orcid.org/0000-0001-5115-9255)
- Xinbao Wu (ORCID: https://orcid.org/0000-0003-3136-1688)
- Yufeng Ge (ORCID: https://orcid.org/0000-0002-4968-6520)
- Yanzhen Liu (ORCID: https://orcid.org/0000-0003-3766-1171)
- Yu Wang (ORCID: https://orcid.org/0000-0003-0467-6465)
- Jixuan Liu (ORCID: https://orcid.org/0000-0001-9703-9224)
- Yunfei Zheng (ORCID: https://orcid.org/0000-0003-4026-2956)
Institutions
- Capital Medical University (CN)
- Peking University (CN)
- Beijing Jishuitan Hospital (CN)
- Huazhong University of Science and Technology (CN)
- Beihang University (CN)
Publication Details
- Journal
- Communications Medicine
- Published
- 2025-11-15
- DOI
- https://doi.org/10.1038/s43856-025-01238-2
- Citations
- 1
- Primary Topic
- Pelvic and Acetabular Injuries
- Type
- article
- Field-Weighted Citation Impact
- 2.01
Funders
- National Natural Science Foundation of China