Comprehensive Summary
Wei et al. conducted a bibliometric study that charted the trends on AI research in prostate cancer (PCa). They used CiteSpace to analyze over 2,500 publications ranging from 2014 to 2024. The authors noticed a sharp increase in publications around 2020, which reflects the rapid AI growth in medical imaging, digital pathology, and overall clinical implications. The two countries with the largest volume of publications were the United States and China. Most of the research was done in disciplines of radiology and oncology. Keyword and reference analyses reflect a shift from early machine-learning approaches to deep learning in radiomics, prostate MRI segmentation, and automated Gleason grading. More recent publications focus on topics of digital pathology and “PI-RADS” (Prostate Imaging Reporting and Data System), which highlights the growing interest in AI tools to improve prostate MRI reading and digital pathology workflows.
Outcomes and Implications
This study shows how quickly AI has become an integral part of PCa research. It underscores its expanding role in diagnosis, prognosis, and treatment planning. The paper displays a strong emphasis on use of AI for imaging and pathology, where AI may help reduce reader variability, improve cancer detection, and streamline workflow. At the same time, the authors highlighted underexplored areas, such as AI in active surveillance, treatment response monitoring, and patient-reported outcomes. These areas represent important opportunities for future research and development. As the field grows, standardized reporting and more strict validation will be essential for translating AI advances into reliable clinical tools.