IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i18p11597-d915224.html
   My bibliography  Save this article

Global Research Trends of Artificial Intelligence on Histopathological Images: A 20-Year Bibliometric Analysis

Author

Listed:
  • Wentong Zhou

    (Center for System Biology, Data Sciences, and Reproductive Health, School of Basic Medical Science, Central South University, Changsha 410031, China)

  • Ziheng Deng

    (Center for System Biology, Data Sciences, and Reproductive Health, School of Basic Medical Science, Central South University, Changsha 410031, China)

  • Yong Liu

    (Center for System Biology, Data Sciences, and Reproductive Health, School of Basic Medical Science, Central South University, Changsha 410031, China)

  • Hui Shen

    (Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University School, New Orleans, LA 70112, USA)

  • Hongwen Deng

    (Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University School, New Orleans, LA 70112, USA
    These authors contributed equally to this work.)

  • Hongmei Xiao

    (Center for System Biology, Data Sciences, and Reproductive Health, School of Basic Medical Science, Central South University, Changsha 410031, China
    These authors contributed equally to this work.)

Abstract

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.

Suggested Citation

  • Wentong Zhou & Ziheng Deng & Yong Liu & Hui Shen & Hongwen Deng & Hongmei Xiao, 2022. "Global Research Trends of Artificial Intelligence on Histopathological Images: A 20-Year Bibliometric Analysis," IJERPH, MDPI, vol. 19(18), pages 1-15, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11597-:d:915224
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/18/11597/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/18/11597/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Donthu, Naveen & Kumar, Satish & Mukherjee, Debmalya & Pandey, Nitesh & Lim, Weng Marc, 2021. "How to conduct a bibliometric analysis: An overview and guidelines," Journal of Business Research, Elsevier, vol. 133(C), pages 285-296.
    2. Andre Esteva & Brett Kuprel & Roberto A. Novoa & Justin Ko & Susan M. Swetter & Helen M. Blau & Sebastian Thrun, 2017. "Correction: Corrigendum: Dermatologist-level classification of skin cancer with deep neural networks," Nature, Nature, vol. 546(7660), pages 686-686, June.
    3. Xiaodong Wang & Ying Chen & Yunshu Gao & Huiqing Zhang & Zehui Guan & Zhou Dong & Yuxuan Zheng & Jiarui Jiang & Haoqing Yang & Liming Wang & Xianming Huang & Lirong Ai & Wenlong Yu & Hongwei Li & Chan, 2021. "Predicting gastric cancer outcome from resected lymph node histopathology images using deep learning," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    4. Chaomei Chen & Fidelia Ibekwe-SanJuan & Jianhua Hou, 2010. "The structure and dynamics of cocitation clusters: A multiple-perspective cocitation analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1386-1409, July.
    5. Chaomei Chen & Loet Leydesdorff, 2014. "Patterns of connections and movements in dual-map overlays: A new method of publication portfolio analysis," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(2), pages 334-351, February.
    6. Andre Esteva & Brett Kuprel & Roberto A. Novoa & Justin Ko & Susan M. Swetter & Helen M. Blau & Sebastian Thrun, 2017. "Dermatologist-level classification of skin cancer with deep neural networks," Nature, Nature, vol. 542(7639), pages 115-118, February.
    7. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cailin Wang & Jidong Wu & Xin He & Mengqi Ye & Wenhui Liu & Rumei Tang, 2018. "Emerging Trends and New Developments in Disaster Research after the 2008 Wenchuan Earthquake," IJERPH, MDPI, vol. 16(1), pages 1-19, December.
    2. Yuhanis Ladewi & Meiryani Meiryani & Ahmad Syamil & Agustini Agustini & Agustinus Winoto, 2024. "The Relation between Climate Change and Carbon Emission Trading: A Bibliometric Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 14(1), pages 686-697, January.
    3. Busra Yiğit & Bünyamin Yasin Çakmak, 2024. "Discovering Psychological Well-Being: A Bibliometric Review," Journal of Happiness Studies, Springer, vol. 25(5), pages 1-24, June.
    4. Keng Yang & Hanying Qi, 2022. "Research on Health Disparities Related to the COVID-19 Pandemic: A Bibliometric Analysis," IJERPH, MDPI, vol. 19(3), pages 1-25, January.
    5. Jianhua Hou & Xiucai Yang & Chaomei Chen, 2018. "Emerging trends and new developments in information science: a document co-citation analysis (2009–2016)," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 869-892, May.
    6. Panetta, Ida Claudia & Leo, Sabrina & Delle Foglie, Andrea, 2023. "The development of digital payments – Past, present, and future – From the literature," Research in International Business and Finance, Elsevier, vol. 64(C).
    7. Gisleine Carmo & Luiz Flávio Felizardo & Valderí Castro Alcântara & Cristiane Aparecida Silva & José Willer Prado, 2023. "The impact of Jürgen Habermas’s scientific production: a scientometric review," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1853-1875, March.
    8. Yao Xiao & Ziheng Deng & Hangjing Tan & Tiejian Jiang & Zhiheng Chen, 2022. "Bibliometric Analysis of the Knowledge Base and Future Trends on Sarcopenia from 1999–2021," IJERPH, MDPI, vol. 19(14), pages 1-17, July.
    9. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    10. Migliavacca, Milena & Goodell, John W. & Paltrinieri, Andrea, 2023. "A bibliometric review of portfolio diversification literature," International Review of Financial Analysis, Elsevier, vol. 90(C).
    11. Gour Gobinda Goswami & Tahmid Labib, 2022. "Modeling COVID-19 Transmission Dynamics: A Bibliometric Review," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
    12. Lin Lu & Laurent Dercle & Binsheng Zhao & Lawrence H. Schwartz, 2021. "Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    13. Zheng Yan & Wenqian Robertson & Yaosheng Lou & Tom W. Robertson & Sung Yong Park, 2021. "Finding leading scholars in mobile phone behavior: a mixed-method analysis of an emerging interdisciplinary field," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9499-9517, December.
    14. Sabina Kordana-Obuch & Michał Wojtoń & Mariusz Starzec & Beata Piotrowska, 2023. "Opportunities and Challenges for Research on Heat Recovery from Wastewater: Bibliometric and Strategic Analyses," Energies, MDPI, vol. 16(17), pages 1-36, September.
    15. Lin Hu & Qinghai Chen & Tingting Yang & Chuanjian Yi & Jing Chen, 2024. "Visualization and Analysis of Hotspots and Trends in Seafood Cold Chain Logistics Based on CiteSpace, VOSviewer, and RStudio Bibliometrix," Sustainability, MDPI, vol. 16(15), pages 1-22, July.
    16. Germán López Pérez & Isabel María García Sánchez & José Luis Zafra Gómez, 2024. "A systematic literature review and bibliometric analysis of eco‐innovation on financial performance: Identifying barriers and drivers," Business Strategy and the Environment, Wiley Blackwell, vol. 33(2), pages 1321-1340, February.
    17. Jin Su & Mo Wang & Mohd Adib Mohammad Razi & Norlida Mohd Dom & Noralfishah Sulaiman & Lai-Wai Tan, 2023. "A Bibliometric Review of Nature-Based Solutions on Urban Stormwater Management," Sustainability, MDPI, vol. 15(9), pages 1-23, April.
    18. Freddy Gabbay & Rotem Lev Aharoni & Ori Schweitzer, 2022. "Deep Neural Network Memory Performance and Throughput Modeling and Simulation Framework," Mathematics, MDPI, vol. 10(21), pages 1-20, November.
    19. Futao Zhang & Yuedong Liu & Yueling Zhang, 2023. "Bibliometric Analysis of Research Trends in Agricultural Soil Organic Carbon Mineralization from 2000 to 2022," Agriculture, MDPI, vol. 13(6), pages 1-19, June.
    20. Ooms, Tahnee & Klaser, Klaudijo & Ishkanian, Armine, 2023. "The role of academia practice partnerships in the well-being economy: Retracing synergies between health and social sciences using bibliometric analysis," Health Policy, Elsevier, vol. 138(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11597-:d:915224. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.