Artificial Intelligence Approach in Prostate CancerDiagnosis: Bibliometric Analysis

dc.contributor.authorДенисенко, Анастасія Петрівна
dc.contributor.authorДенисенко, Анастасия Петровна
dc.contributor.authorDenysenko, Anastasiia Petrivna
dc.contributor.authorСавченко, Тарас Русланович
dc.contributor.authorСавченко, Тарас Русланович
dc.contributor.authorSavchenko, Taras Ruslanovych
dc.contributor.authorДовбиш, Анатолій Степанович
dc.contributor.authorДовбыш, Анатолий Степанович
dc.contributor.authorDovbysh, Anatolii Stepanovych
dc.contributor.authorРоманюк, Анатолій Миколайович
dc.contributor.authorРоманюк, Анатолий Николаевич
dc.contributor.authorRomaniuk, Anatolii Mykolaiovych
dc.contributor.authorМоскаленко, Роман Андрійович
dc.contributor.authorМоскаленко, Роман Андреевич
dc.contributor.authorMoskalenko, Roman Andriiovych
dc.date.accessioned2022-08-17T08:02:41Z
dc.date.available2022-08-17T08:02:41Z
dc.date.issued2022
dc.description.abstractBackground.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.en_US
dc.identifier.citationDenysenko, 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.2022.2.5en_US
dc.identifier.sici0000-0001-9223-782Xen
dc.identifier.urihttps://essuir.sumdu.edu.ua/handle/123456789/88998
dc.language.isoenen_US
dc.publisherIvano-Frankivsk National Medical Universityen_US
dc.rights.uriCC BY-NC 4.0en_US
dc.subjectArtificial Intelligenceen_US
dc.subjectProstate Canceren_US
dc.subjectGleason Scoreen_US
dc.subjectBibliometric Analysisen_US
dc.titleArtificial Intelligence Approach in Prostate CancerDiagnosis: Bibliometric Analysisen_US
dc.typeArticleen_US

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