Research status and trends of deep learning in colorectal cancer (2011-2023): Bibliometric analysis and visualization

This study highlights the current status and most active directions of the use of DL in CRC. This approach has important applications in the identification, diagnosis, localization, classification and prognosis of the disease and will remain a central focus in the future.

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Publication Details

Journal
World Journal of Gastrointestinal Oncology
Published
2025-05-15
DOI
https://doi.org/10.4251/wjgo.v17.i5.103667
Citations
1
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
1.36
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Research status and trends of deep learning in colorectal cancer (2011-2023): Bibliometric analysis and visualization

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1 citations
World Journal of Gastrointestinal Oncology
Radiomics and Machine Learning in Medical Imaging
1.36
article

Research status and trends of deep learning in colorectal cancer (2011-2023): Bibliometric analysis and visualization

Hongxing Zhao, L Qi, Jingnan Xue, Jieqiong Chen, Hu-Po Bian, B. Li
article en
1 citations

Abstract

This study highlights the current status and most active directions of the use of DL in CRC. This approach has important applications in the identification, diagnosis, localization, classification and prognosis of the disease and will remain a central focus in the future.

World Journal of Gastrointestinal OncologyVol. 17(5)
Huzhou Normal University (CN), Fourth People’s Hospital of Jinan (CN), Third People's Hospital of Huzhou (CN)
Openalex Percentile: Top 20%
Radiomics and Machine Learning in Medical Imaging
1.36
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