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Development trends and knowledge framework of artificial intelligence (AI) applications in oncology by years: a bibliometric analysis from 1992 to 2022.

作者信息

Koçak Murat, Akçalı Zafer

机构信息

Department of Medical Informatics, Faculty of Medicine, Baskent University, Taşkent Caddesi (Eski 1. Cadde) 77. Sokak (Eski 16. Sokak) No:11, 06490, Bahçelievler, Ankara, Turkey.

出版信息

Discov Oncol. 2024 Oct 16;15(1):566. doi: 10.1007/s12672-024-01415-0.


DOI:10.1007/s12672-024-01415-0
PMID:39406991
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11480271/
Abstract

PURPOSE: Oncology is the primary field in medicine with a high rate of artificial intelligence (AI) use. Thus, this study aimed to investigate the trends of AI in oncology, evaluating the bibliographic characteristics of articles. We evaluated the related research on the knowledge framework of Artificial Intelligence (AI) applications in Oncology through bibliometrics analysis and explored the research hotspots and current status from 1992 to 2022. METHODS: The research employed a scientometric methodology and leveraged scientific visualization tools such as Bibliometrix R Package Software, VOSviewer, and Litmaps for comprehensive data analysis. Scientific AI-related publications in oncology were retrieved from the Web of Science (WoS) and InCites from 1992 to 2022. RESULTS: A total of 7,815 articles authored by 35,098 authors and published in 1,492 journals were included in the final analysis. The most prolific authors were Esteva A (citaition = 5,821) and Gillies RJ (citaition = 4288). The most active institutions were the Chinese Academy of Science and Harward University. The leading journals were Frontiers ın Oncology and Scientific Reports. The most Frequent Author Keywords are "machine learning", "deep learning," "radiomics", "breast cancer", "melanoma" and "artificial intelligence," which are the research hotspots in this field. A total of 10,866 Authors' keywords were investigated. The average number of citations per document is 23. After 2015, the number of publications proliferated. CONCLUSION: The investigation of Artificial Intelligence (AI) applications in the field of Oncology is still in its early phases especially for genomics, proteomics, and clinicomics, with extensive studies focused on biology, diagnosis, treatment, and cancer risk assessment. This bibliometric analysis offered valuable perspectives into AI's role in Oncology research, shedding light on emerging research paths. Notably, a significant portion of these publications originated from developed nations. These findings could prove beneficial for both researchers and policymakers seeking to navigate this field.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/a06fd2e1d0ab/12672_2024_1415_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/9cfa63864fb5/12672_2024_1415_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/acb7eef3a4ac/12672_2024_1415_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/33869a65691b/12672_2024_1415_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/d52ac8f7e076/12672_2024_1415_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/fbaef333b048/12672_2024_1415_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/3c04e189665e/12672_2024_1415_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/35be72e8f9b2/12672_2024_1415_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/8ad6568807b6/12672_2024_1415_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/d00c74bbf337/12672_2024_1415_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/e63cc6816513/12672_2024_1415_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/f4786edbf946/12672_2024_1415_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/0a04b0df4c83/12672_2024_1415_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/c2455f9823ea/12672_2024_1415_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/3b0643b4b0b1/12672_2024_1415_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/a06fd2e1d0ab/12672_2024_1415_Fig15_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/9cfa63864fb5/12672_2024_1415_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/acb7eef3a4ac/12672_2024_1415_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/33869a65691b/12672_2024_1415_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/d52ac8f7e076/12672_2024_1415_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/fbaef333b048/12672_2024_1415_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/3c04e189665e/12672_2024_1415_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/35be72e8f9b2/12672_2024_1415_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/8ad6568807b6/12672_2024_1415_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/d00c74bbf337/12672_2024_1415_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/e63cc6816513/12672_2024_1415_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/f4786edbf946/12672_2024_1415_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/0a04b0df4c83/12672_2024_1415_Fig12_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/c2455f9823ea/12672_2024_1415_Fig13_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/3b0643b4b0b1/12672_2024_1415_Fig14_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13bf/11480271/a06fd2e1d0ab/12672_2024_1415_Fig15_HTML.jpg

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引用本文的文献

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The published role of artificial intelligence in drug discovery and development: a bibliometric and social network analysis from 1990 to 2023.

J Cheminform. 2025-5-8

[2]
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[2]
Immune checkpoint inhibitor-related hearing loss: a systematic review and analysis of individual patient data.

Support Care Cancer. 2023-10-11

[3]
Diagnostic Accuracy of Machine Learning AI Architectures in Detection and Classification of Lung Cancer: A Systematic Review.

Diagnostics (Basel). 2023-6-22

[4]
Clinicomics-guided distant metastasis prediction in breast cancer via artificial intelligence.

BMC Cancer. 2023-3-14

[5]
Artificial Intelligence for Cancer Detection-A Bibliometric Analysis and Avenues for Future Research.

Curr Oncol. 2023-1-29

[6]
Hypertransaminasemia in cancer patients receiving immunotherapy and immune-based combinations: the MOUSEION-05 study.

Cancer Immunol Immunother. 2023-6

[7]
Identifying optimal first-line treatment for advanced non-small cell lung carcinoma with high PD-L1 expression: a matter of debate.

Br J Cancer. 2022-11

[8]
Recent Applications of Artificial Intelligence in Early Cancer Detection.

Curr Med Chem. 2022

[9]
Peripheral neuropathy and headache in cancer patients treated with immunotherapy and immuno-oncology combinations: the MOUSEION-02 study.

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[10]
Predicting cardiac adverse events in patients receiving immune checkpoint inhibitors: a machine learning approach.

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