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Title | Artificial Intelligence Approach in Prostate Cancer Diagnosis: Bibliometric Analysis |
Authors |
Denysenko, Anastasiia Petrivna
![]() Savchenko, Taras Ruslanovych ![]() Dovbysh, Anatolii Stepanovych ![]() Romaniuk, Anatolii Mykolaiovych ![]() Moskalenko, Roman Andriiovych ![]() |
ORCID |
http://orcid.org/0000-0001-9223-782X http://orcid.org/0000-0002-9557-073X http://orcid.org/0000-0003-1829-3318 http://orcid.org/0000-0003-2560-1382 http://orcid.org/0000-0002-2342-0337 |
Keywords |
штучний інтелект исскуственный интеллект artificial intelligence рак простати рак простаты prostate cancer шкала Глісона шкала Глисона Gleason score бібліометричний аналіз библиометрический анализ bibliometric analysis |
Type | Article |
Date of Issue | 2022 |
URI | https://essuir.sumdu.edu.ua/handle/123456789/87862 |
Publisher | Івано-Франківський Національний медичний університет |
License | Creative Commons Attribution - NonCommercial 4.0 International |
Citation | Denysenko A., Savchenko T., Dovbysh A., Romaniuk A., Moskalenko R. Artificial Intelligence Approach in Prostate Cancer Diagnosis: Bibliometric Analysis // Galician medical journal. 2022, Vol. 29, Issue 2, E202225. DOI: 10.21802/gmj.2022.2.5 |
Abstract |
Background. Prostate cancer is one of the most common male malignancies worldwide that ranks second
in cancer-related mortality. Artificial intelligence can reduce subjectivity and improve the efficiency of
prostate cancer diagnosis using fewer resources as compared to standard diagnostic scheme.
This review aims to highlight the main concepts of prostate cancer diagnosis and artificial intelligence
application and to determine achievements, current trends, and potential research directions in this field,
using bibliometric analysis.
Materials and Methods. The studies on the application of artificial intelligence in the morphological
diagnosis of prostate cancer for the past 35 years were searched for in the Scopus database using “artificial
intelligence” and “prostate cancer” keywords. The selected studies were systematized using Scopus
bibliometric tools and the VOSviewer software.
Results. The number of publications in this research field has drastically increased since 2016, with most
research carried out in the United States, Canada, and the United Kingdom. They can be divided into three
thematic clusters and three qualitative stages in the development of this research field in timeline aspect.
Conclusions. Artificial intelligence algorithms are now being actively developed, playing a huge role in
the diagnosis of prostate cancer. Further development and improvement of artificial intelligence algorithms
have the potential to automate and standardize the diagnosis of prostate cancer. |
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File | Size | Format | Downloads |
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Denysenko_gmj-29-E202225.pdf | 1.2 MB | Adobe PDF | -1616401276 |
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