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Title Artificial Intelligence Approach in Prostate CancerDiagnosis: 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 Artificial Intelligence
Prostate Cancer
Gleason Score
Bibliometric Analysis
Type Article
Date of Issue 2022
URI https://essuir.sumdu.edu.ua/handle/123456789/88998
Publisher Ivano-Frankivsk National Medical University
License Creative Commons Attribution - NonCommercial 4.0 International
Citation Denysenko, A., Savchenko, T., Dovbysh, A., Romaniuk, A., & Moskalenko, R. (2022). Artificial Intelligence Approach in Prostate Cancer Diagnosis: Bibliometric Analysis. Galician Medical Journal, 29(2), E202225. https://doi.org/10.21802/gmj.2022.2.5
Abstract Background.Prostate cancer is one of the most common male malignancies worldwide that ranks secondin cancer-related mortality. Artificial intelligence can reduce subjectivity and improve the efficiency ofprostate cancer diagnosis using fewer resources as compared to standard diagnostic scheme.This review aimsto highlight the main concepts of prostate cancer diagnosis and artificial intelligenceapplication 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 morphologicaldiagnosis of prostate cancer for the past 35 years were searched for in the Scopus database using “artificialintelligence” and “prostate cancer” keywords. The selected studies were systematized using Scopusbibliometric tools and the VOSviewer software.Results.The number of publications in this research field has drastically increased since 2016, with mostresearch carried out in the United States, Canada, and the United Kingdom. They can be divided into threethematic 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 inthe diagnosis of prostate cancer. Further development and improvement of artificial intelligence algorithmshave the potential to automate and standardize the diagnosis of prostate cancer.
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