A deep learning model for personalized intra-arterial therapy planning in unresectable hepatocellular carcinoma: a multicenter retrospective study
This study received funding from the Beijing Municipal Natural Science Foundation, China (Z190024); the Key Program of the National Natural Science Foundation of China, China (81930119); The Science and Technology Planning Program of Beijing Municipal Science & Technology Commission and Administrative Commission of Zhongguancun Science Park, China (Z231100004823012); Tsinghua University Initiative Scientific Research Program of Precision Medicine, China (10001020108); and Institute for Intelligent Healthcare, Tsinghua University, China (041531001).
Authors
- Qian Lü (ORCID: https://orcid.org/0000-0003-2388-0357)
- Ziming Xu
- Jiaqi Dou (ORCID: https://orcid.org/0009-0001-6842-9378)
- Shuiqing Zhuo (ORCID: https://orcid.org/0000-0001-9833-5543)
- Chao An (ORCID: https://orcid.org/0000-0003-4029-2709)
- Runyu Yang (ORCID: https://orcid.org/0000-0002-3669-4249)
- Ran Wei (ORCID: https://orcid.org/0000-0003-4293-6686)
- Xiaoqi Lin
- Huijun Chen (ORCID: https://orcid.org/0000-0003-1158-5510)
- Haozhong Sun (ORCID: https://orcid.org/0000-0003-1523-7089)
- Rui Li (ORCID: https://orcid.org/0009-0009-8136-4159)
Institutions
- Sun Yat-sen University (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Sun Yat-sen University Cancer Center (CN)
- Beijing Tsinghua Chang Gung Hospital (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- EClinicalMedicine
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1016/j.eclinm.2024.102808
- Citations
- 11
- Primary Topic
- Hepatocellular Carcinoma Treatment and Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 4.06
Funders
- National Natural Science Foundation of China