Global trends in machine learning applied to clinical research in liver cancer: Bibliometric and visualization analysis (2001-2024)

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 an...

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Veröffentlicht in:Medicine (Baltimore) 2024-12, Vol.103 (49), p.e40790
Hauptverfasser: Zhuo, Enba, Yang, Wenzhi, Wang, Yafen, Tang, Yanchao, Wang, Wanrong, Zhou, Lingyan, Chen, Yanjun, Li, Pengman, Chen, Bangjie, Gao, Weimin, Liu, Wang
Format: Artikel
Sprache:eng
Schlagworte:
Bibliometrics
Biomedical Research - statistics & numerical data
Biomedical Research - trends
Humans
Liver Neoplasms
Machine Learning - trends
Narrative Review
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Beschreibung
Zusammenfassung: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.
ISSN:1536-5964
0025-7974
1536-5964
DOI:10.1097/MD.0000000000040790