Radiomics to predict PNI in ESCC
CECT-based radiomics analysis, particularly utilizing the RF, can noninvasively predict the PNI in ESCC preoperatively. This novel approach could enhance patient management by providing personalized information, thereby facilitating the development of individualized treatment strategies for ESCC patients.
Authors
- Jialiang Ren (ORCID: https://orcid.org/0000-0001-5616-7035)
- Ai‐Jun Miao (ORCID: https://orcid.org/0000-0001-7681-2038)
- Qi Wang (ORCID: https://orcid.org/0000-0003-0858-9393)
- Xiaopeng Zhao (ORCID: https://orcid.org/0000-0002-0557-8579)
- Xiaolong Gu (ORCID: https://orcid.org/0000-0001-8549-342X)
- S S Li
- Andu Zhang
- Yang Li (ORCID: https://orcid.org/0000-0002-1909-2174)
- Xiangming Wang (ORCID: https://orcid.org/0000-0002-3751-3868)
- Huiyan Deng (ORCID: https://orcid.org/0000-0001-7524-3486)
- Gaofeng Shi (ORCID: https://orcid.org/0000-0001-5832-1462)
- Li Yang (ORCID: https://orcid.org/0000-0003-1347-3934)
Institutions
- Hebei Medical University (CN)
- Hengshui University (CN)
- Fourth Hospital of Hebei Medical University (CN)
Publication Details
- Journal
- Abdominal Radiology
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1007/s00261-024-04562-8
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00