From texture analysis to artificial intelligence: global research landscape and evolutionary trajectory of radiomics in hepatocellular carcinoma
Radiomics in HCC represents a rapidly expanding, AI-driven field characterized by extensive multidisciplinary collaboration. Future priorities should emphasize standardization, large-scale multicenter validation, enhanced international cooperation, and clinical translation to maximize radiomics' potential in precision HCC oncology.
Authors
- Tao Peng (ORCID: https://orcid.org/0000-0001-6133-7078)
- Xiong Teng (ORCID: https://orcid.org/0000-0002-5535-5066)
- Qiuju Luo (ORCID: https://orcid.org/0000-0002-6697-1390)
- Yidi Chen (ORCID: https://orcid.org/0000-0001-6293-4624)
Institutions
- Guangxi University (CN)
- Sun Yat-sen University (CN)
- Guangxi Medical University (CN)
- The Seventh Affiliated Hospital of Sun Yat-sen University (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
- Tumor Hospital of Guangxi Medical University (CN)
Publication Details
- Journal
- Discover Oncology
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1007/s12672-025-03620-x
- Citations
- 3
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangxi Province
- Guangxi Medical University