ReviewTherapeutic advances in urology
Radiomics in prostate cancer: an up-to-date review.
Review in Therapeutic advances in urology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06565923 (Study on the Staging and Prognosis Model of Bladder Cancer Based on Artificial Intelligence and Multimodal Omics Features), which is not on this map. Cited by 84 papers, 6 of them syntheses that pooled it.
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.
Study on the Staging and Prognosis Model of Bladder Cancer Based on Artificial Intelligence and Multimodal Omics Features
Who cites it
84 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- The Role of Artificial Intelligence in the Characterization and Outcome Prediction of Prostate Cancer: A Systematic Review.Tomography (Ann Arbor, Mich.) · 2026Pooled it
- MRI-based radiomics for prediction of biochemical recurrence in prostate cancer: a systematic review and meta-analysis.Abdominal radiology (New York) · 2025Pooled it
- Application of radiomics-based prediction model to predict preoperative lymph node metastasis in prostate cancer: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
- Delta radiomics: an updated systematic review.La Radiologia medica · 2024Pooled it
- Bibliometric and visual analysis of radiomics for evaluating lymph node status in oncology.Frontiers in medicine · 2024Pooled it
- Efficacy and safety of salvage radiotherapy combined with endocrine therapy in patients with biochemical recurrence after radical prostatectomy: A systematic review and meta-analysis of randomized controlled trials.Frontiers in oncology · 2022Pooled it
- Prediction of distant metastasis in esophageal cancer using a radiomics-clinical model.European journal of medical research · 2022Trial
- [Between catheters and artificial intelligence: High-tech urology-where manual skills meet digital expertise].Urologie (Heidelberg, Germany) · 2026Review
- Article
- Interpretable machine learning model of contrast-enhanced CT radiomics for predicting post-BCG recurrence in high-grade non-muscle-invasive bladder cancer.World journal of urology · 2026Article
- Imaging Biomarkers in Radiotherapy.Cancers · 2026Review
- From STORM to steadier ground: refining radiotherapy for nodal oligorecurrent prostate cancer.Translational andrology and urology · 2026Article
- Cancer classification with radiomics in controlled preclinical models.Scientific reports · 2026Article
- PSMA-Based Radiopharmaceuticals in Prostate Cancer Theranostics: Imaging, Clinical Advances, and Future Directions.Cancers · 2026Review
- Non-invasive prediction of lymph node involvement in prostate cancer via machine learning on whole-prostate MRI.Frontiers in oncology · 2026Article
- Article
- Diagnostic accuracy of MRI radiomics in predicting lymph node metastasis in prostate cancer: A systematic review.European journal of radiology open · 2025Review
- Next-Generation Advances in Prostate Cancer Imaging and Artificial Intelligence Applications.Journal of imaging · 2025Review
- Predicting bone metastasis and high-grade Gleason scores in prostate cancer: a retrospective study integrating clinical features and magnetic resonance imaging radiomics.Translational andrology and urology · 2025Article
- Beyond Radiomics Alone: Enhancing Prostate Cancer Classification with ADC Ratio in a Multicenter Benchmarking Study.Diagnostics (Basel, Switzerland) · 2025Article
24 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications.
Indexed as
Identifiers
What Socratic 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 Socratic graph.