Bibliometric review maps research trends and collaboration networks in machine learning applications for prostate cancer, suggesting areas for future studies.
Key Points
Machine learning applications in prostate cancer research have surged exponentially, particularly after 2021, indicating a growing interest in this field.
A total of 2,632 publications were identified, with 661 published in 2024 alone, emphasizing the rapid increase in research output over recent years.
Analytical tools like CiteSpace and VOSviewer were utilized in a systematic bibliometric review that assessed publication trends and collaboration networks.
The findings highlight the need for interdisciplinary collaboration and prospective multicenter validation studies to bridge the translational gap in prostate cancer therapies.