Keywords
Prostate Cancer
Gleason Score
Bibliometric Analysis
How to Cite
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.
References
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