ArticleJU open plus2025
Population-Specific Radiomics From Biparametric Magnetic Resonance Imaging Improves Prostate Cancer Risk Stratification in African American Men.
Article in JU open plus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Variability Regularized Feature Selection (VaRFS) for optimal identification of robust and discriminable features from medical imaging.Npj imaging · 2026Article
- Perspective on the integration of radiomics and spatial omics in the analysis of the tumor microenvironment of bladder cancer and prospects for precision diagnosis and treatment.Frontiers in immunology · 2026Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Purpose: To quantify population-specific differences in prostate cancer (PCa) presentation between African American (AA) and White (W) men on MRI using radiomics. Materials and Methods: We identified N = 149 men with PCa who underwent 3T MRI, a confirmatory biopsy and for whom self-reported race was available. Patient studies were partitioned into training (D Results: Radiomic features from PCa ROIs on biparametric MRI associated with csPCa were observed to be different in AA compared with W men, especially in the peritumoral region. Population-specific radiomic models outperformed similarly trained C Conclusions: Accounting for population-specific differences in radiomics may enable improved PCa risk stratification at MRI among AA men compared with a population agnostic approach.
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