Global trends in machine learning applied to clinical research in liver cancer: Bibliometric and visualization analysis (2001–2024)
This study explores the intersection of liver cancer and machine learning through bibliometric analysis. The aim is to identify highly cited papers in the field and examine the current research landscape, highlighting emerging trends and key areas of focus in liver cancer and machine learning. By analyzing citation patterns, this study sheds light on the evolving role of machine learning in liver cancer research and its potential for future advancements.
Authors
- W.H.D. Liu
- Weimin Gao (ORCID: https://orcid.org/0000-0002-6758-9775)
- Ping Li (ORCID: https://orcid.org/0000-0003-1484-117X)
- Lingyan Zhou (ORCID: https://orcid.org/0000-0002-5138-5188)
- Wanrong Wang (ORCID: https://orcid.org/0000-0002-5516-3056)
- Enba Zhuo (ORCID: https://orcid.org/0009-0008-0723-8501)
- Yanjun Chen (ORCID: https://orcid.org/0009-0008-6047-6867)
- Yanchao Tang
- Yafen Wang (ORCID: https://orcid.org/0000-0001-8641-0411)
- Bangjie Chen (ORCID: https://orcid.org/0000-0003-0601-0480)
- Wenzhi Yang
Institutions
- Anhui Medical University (CN)
- Sanya Central Hospital (CN)
- First Affiliated Hospital of Anhui Medical University (CN)
- S.P.E.C.I.E.S. (US)
Publication Details
- Journal
- Medicine
- Published
- 2024-12-06
- DOI
- https://doi.org/10.1097/md.0000000000040790
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00