To predict cervical lymph node tuberculosis based on clinical-multimodal ultrasound radiomics model
The Multimodal ultrasound radiomics combined with clinical manifestations and imaging features, showed good judgment in identifying CLNT ability and good stability.
Authors
- Xiangyu Meng (ORCID: https://orcid.org/0000-0002-7703-1177)
- Ting Lin
- Jiahui Tong (ORCID: https://orcid.org/0000-0001-5435-6326)
- Jiaqi Luo (ORCID: https://orcid.org/0000-0001-6903-8515)
- Gaoyi Yang
- Yuehui Yu (ORCID: https://orcid.org/0000-0001-7794-0787)
- Peijun Chen (ORCID: https://orcid.org/0000-0002-6076-1894)
- Ying Zhang (ORCID: https://orcid.org/0000-0002-4369-7448)
- Xinyi Yan (ORCID: https://orcid.org/0009-0004-5657-7105)
- Ying Wang (ORCID: https://orcid.org/0009-0008-3662-2692)
Institutions
- Zhejiang Chinese Medical University (CN)
- Hangzhou Normal University (CN)
- Westlake University (CN)
- Zhejiang Provincial People's Hospital (CN)
- Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
- Hangzhou Red Cross Hospital (CN)
Publication Details
- Journal
- Clinical Hemorheology and Microcirculation
- Published
- 2025-04-01
- DOI
- https://doi.org/10.1177/13860291241304060
- Citations
- 1
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.36