ReviewJournal of the Korean Society of Radiology2025
AI in Prostate MRI: A Task-Based Review.
Review in Journal of the Korean Society of Radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- [Preface to the Special Issue on Update in Prostate MRI].Journal of the Korean Society of Radiology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prostate MRI is widely employed across the clinical pathway of prostate cancer, including detection, staging, treatment planning, and surveillance. With the increasing demand for consistent and efficient image interpretation, AI has gained considerable attention as a supportive tool in prostate MRI. This review provides a task-based overview of AI applications in prostate MRI, addressing key areas such as prostate gland segmentation, cancer detection and risk stratification, local staging, disease monitoring during active surveillance, recurrence detection, and image quality assessment. Across these tasks, AI, particularly deep learning, has demonstrated promising results. Although only a limited number of AI tools for prostate MRI are commercially available, it remains essential for radiologists to understand how AI can support clinical practice, particularly as further advances are anticipated.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.