Artificial Intelligence for Cancer Detection—A Bibliometric Analysis and Avenues for Future Research
After cardiovascular diseases, cancer is responsible for the most deaths worldwide. Detecting a cancer disease early improves the chances for healing significantly. One group of technologies that is increasingly applied for detecting cancer is artificial intelligence. Artificial intelligence has gre...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-01-01
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| Series: | Current Oncology |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1718-7729/30/2/125 |
| _version_ | 1797621566471667712 |
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| author | Erik Karger Marko Kureljusic |
| author_facet | Erik Karger Marko Kureljusic |
| author_sort | Erik Karger |
| collection | DOAJ |
| description | After cardiovascular diseases, cancer is responsible for the most deaths worldwide. Detecting a cancer disease early improves the chances for healing significantly. One group of technologies that is increasingly applied for detecting cancer is artificial intelligence. Artificial intelligence has great potential to support clinicians and medical practitioners as it allows for the early detection of carcinomas. During recent years, research on artificial intelligence for cancer detection grew a lot. Within this article, we conducted a bibliometric study of the existing research dealing with the application of artificial intelligence in cancer detection. We analyzed 6450 articles on that topic that were published between 1986 and 2022. By doing so, we were able to give an overview of this research field, including its key topics, relevant outlets, institutions, and articles. Based on our findings, we developed a future research agenda that can help to advance research on artificial intelligence for cancer detection. In summary, our study is intended to serve as a platform and foundation for researchers that are interested in the potential of artificial intelligence for detecting cancer. |
| first_indexed | 2024-03-11T08:57:50Z |
| format | Article |
| id | doaj.art-51375fd98bb442849996fb2f327a848c |
| institution | Directory Open Access Journal |
| issn | 1198-0052 1718-7729 |
| language | English |
| last_indexed | 2024-03-11T08:57:50Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Current Oncology |
| spelling | doaj.art-51375fd98bb442849996fb2f327a848c2023-11-16T19:57:39ZengMDPI AGCurrent Oncology1198-00521718-77292023-01-013021626164710.3390/curroncol30020125Artificial Intelligence for Cancer Detection—A Bibliometric Analysis and Avenues for Future ResearchErik Karger0Marko Kureljusic1Information Systems and Strategic IT Management, University of Duisburg-Essen, 45141 Essen, GermanyInternational Accounting, University of Duisburg-Essen, 45141 Essen, GermanyAfter cardiovascular diseases, cancer is responsible for the most deaths worldwide. Detecting a cancer disease early improves the chances for healing significantly. One group of technologies that is increasingly applied for detecting cancer is artificial intelligence. Artificial intelligence has great potential to support clinicians and medical practitioners as it allows for the early detection of carcinomas. During recent years, research on artificial intelligence for cancer detection grew a lot. Within this article, we conducted a bibliometric study of the existing research dealing with the application of artificial intelligence in cancer detection. We analyzed 6450 articles on that topic that were published between 1986 and 2022. By doing so, we were able to give an overview of this research field, including its key topics, relevant outlets, institutions, and articles. Based on our findings, we developed a future research agenda that can help to advance research on artificial intelligence for cancer detection. In summary, our study is intended to serve as a platform and foundation for researchers that are interested in the potential of artificial intelligence for detecting cancer.https://www.mdpi.com/1718-7729/30/2/125cancer detectionartificial intelligencemachine learningdeep learningbibliometric study |
| spellingShingle | Erik Karger Marko Kureljusic Artificial Intelligence for Cancer Detection—A Bibliometric Analysis and Avenues for Future Research Current Oncology cancer detection artificial intelligence machine learning deep learning bibliometric study |
| title | Artificial Intelligence for Cancer Detection—A Bibliometric Analysis and Avenues for Future Research |
| title_full | Artificial Intelligence for Cancer Detection—A Bibliometric Analysis and Avenues for Future Research |
| title_fullStr | Artificial Intelligence for Cancer Detection—A Bibliometric Analysis and Avenues for Future Research |
| title_full_unstemmed | Artificial Intelligence for Cancer Detection—A Bibliometric Analysis and Avenues for Future Research |
| title_short | Artificial Intelligence for Cancer Detection—A Bibliometric Analysis and Avenues for Future Research |
| title_sort | artificial intelligence for cancer detection a bibliometric analysis and avenues for future research |
| topic | cancer detection artificial intelligence machine learning deep learning bibliometric study |
| url | https://www.mdpi.com/1718-7729/30/2/125 |
| work_keys_str_mv | AT erikkarger artificialintelligenceforcancerdetectionabibliometricanalysisandavenuesforfutureresearch AT markokureljusic artificialintelligenceforcancerdetectionabibliometricanalysisandavenuesforfutureresearch |