Artificial intelligence-assisted multimodal imaging for the clinical applications of breast cancer: a bibliometric analysis
AI-assisted multimodal imaging has significantly advanced BC diagnosis and management, with promising future developments. This study offers researchers a comprehensive overview of current frameworks and emerging research directions. Future efforts are expected to focus on improving diagnostic precision and refining therapeutic strategies through optimized imaging techniques and AI algorithms, emphasizing international collaboration to drive innovation and clinical translation.
Authors
- Zhifeng Ye
- Ting Huang (ORCID: https://orcid.org/0009-0001-2377-0855)
- Junhua Guo
- Heran Zhou (ORCID: https://orcid.org/0009-0002-2519-2654)
- Keke Hu (ORCID: https://orcid.org/0000-0002-6663-6832)
- Chang Hou (ORCID: https://orcid.org/0000-0003-4883-068X)
Institutions
- Zhejiang Chinese Medical University (CN)
- Hangzhou Hospital of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1007/s12672-025-02329-1
- Citations
- 6
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 8.16