Wentong Zhou
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Wentong Zhou has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Hong-Mei Xiao
Center for System Biology, Data Sciences, and Reproductive Health, School of Basic Medical Science, Central South University , 172 Tongzipo Road, Yuelu District, Changsha 410013, Hunan Province
1 shared publication - Hong-Wen Deng
School of Medicine, Tulane University, New Orleans, LA, USA
1 shared publication - Hui Shen
School of Medicine, Tulane University, New Orleans, LA, USA
1 shared publication - Yong Liu
Center for System Biology, Data Sciences, and Reproductive Health, School of Basic Medical Science, Central South University, Changsha 410031, China
1 shared publication - Ziheng Deng
Center for System Biology, Data Sciences, and Reproductive Health, School of Basic Medical Science, Central South University, Changsha 410031, China
1 shared publication
Latest Publications
- Open Access
- 15 September 2022
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 19 (18) , 11597
Global Research Trends of Artificial Intelligence on Histopathological Images: A 20-Year Bibliometric Analysis
Cancer has become a major threat to global health care. With the development of computer science, artificial intelligence (AI) has been widely applied in histopathological images (HI) analysis. This study analyzed the publications of AI in HI from 2001 to 2021 by bibliometrics, exploring the research status and the potential popular directions in the future. A total of 2844 publications from the Web of Science Core Collection were included in the bibliometric analysis. The country/region, institution, author, journal, keyword, and references were analyzed by using VOSviewer and CiteSpace. The results showed that the number of publications has grown rapidly in the last five years. The USA is the most productive and influential country with 937 publications and 23,010 citations, and most of the authors and institutions with higher numbers of publications and citations are from the USA. Keyword analysis showed that breast cancer, prostate cancer, colorectal cancer, and lung cancer are the tumor types of greatest concern. Co-citation analysis showed that classification and nucleus segmentation are the main research directions of AI-based HI studies. Transfer learning and self-supervised learning in HI is on the rise. This study performed the first bibliometric analysis of AI in HI from multiple indicators, providing insights for researchers to identify key cancer types and understand the research trends of AI application in HI.
- 15 September 2022
- Published by MDPI AG in International Journal of Environmental Research and Public Health
- Vol. 19 (18) , 11597
Open AccessGlobal Research Trends of Artificial Intelligence on Histopathological Images: A 20-Year Bibliometric Analysis
Cancer has become a major threat to global health care. With the development of computer science, artificial intelligence (AI) has been widely applied in histopathological images (HI) analysis. This study analyzed the publications of AI in HI from 2001 to 2021 by bibliometrics, exploring the research status and the potential popular directions in the future. A total of 2844 publications from the Web of Science Core Collection were included in the bibliometric analysis. The country/region, institution, author, journal, keyword, and references were analyzed by using VOSviewer and CiteSpace. The results showed that the number of publications has grown rapidly in the last five years. The USA is the most productive and influential country with 937 publications and 23,010 citations, and most of the authors and institutions with higher numbers of publications and citations are from the USA. Keyword analysis showed that breast cancer, prostate cancer, colorectal cancer, and lung cancer are the tumor types of greatest concern. Co-citation analysis showed that classification and nucleus segmentation are the main research directions of AI-based HI studies. Transfer learning and self-supervised learning in HI is on the rise. This study performed the first bibliometric analysis of AI in HI from multiple indicators, providing insights for researchers to identify key cancer types and understand the research trends of AI application in HI.