Predicting Postoperative Prognosis in Pediatric Malignant Tumor With MRI Radiomics and Deep Learning Models: A Retrospective Study
The multimodal model demonstrated effective prediction of the 3-year postoperative DFS in pediatric brain tumors, offering a scientific foundation for personalized treatment.
Authors
- Ting Fan (ORCID: https://orcid.org/0000-0001-8286-0896)
- Yongde Zhou (ORCID: https://orcid.org/0000-0003-4789-8674)
- Xuan Zhou (ORCID: https://orcid.org/0000-0002-6896-6990)
- Yao Chen (ORCID: https://orcid.org/0000-0002-7120-0902)
- Cuiping Yu
- Baoguo Wang (ORCID: https://orcid.org/0000-0001-8299-283X)
- Jianfeng Yu (ORCID: https://orcid.org/0000-0003-1893-965X)
- Xin‐Hua Hu (ORCID: https://orcid.org/0000-0001-5038-7651)
Institutions
- Capital Medical University (CN)
- Beijing Sanbo Brain Hospital (CN)
- Chinese People's Liberation Army (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Journal of Craniofacial Surgery
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1097/scs.0000000000011466
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36