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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.
Appears in Collections: Наукові видання (НН МІ)

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