ArticleCurrent oncology (Toronto, Ont.)2024
Clinically Significant Prostate Cancer Prediction Using Multimodal Deep Learning with Prostate-Specific Antigen Restriction.
Article in Current oncology (Toronto, Ont.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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.
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Who cites it
6 citing papers in PubMed.
- Recent advances in discriminating prostate cancer from benign prostatic diseases in the pre-biopsy population.Medical oncology (Northwood, London, England) · 2026Review
- Artificial intelligence in urological malignancy diagnosis and prognosis: current status and future prospects.The Canadian journal of urology · 2026Review
- Artificial intelligence for prostate cancer detection and risk stratification using transrectal ultrasound: a narrative review.Gland surgery · 2026Review
- Multimodal artificial intelligence in urologic precision oncology: from algorithm to translational medicine (a systemized narrative review).Frontiers in oncology · 2026Review
- Tumor microenvironment-mediated immune evasion and resistance in prostate cancer: mechanisms, cross-talk, and therapeutic opportunities.Clinical and experimental medicine · 2025Review
- Integrative analysis of blood biomarkers and clinical variables improves early detection of aggressive prostate cancer.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
19 authors.
Funding
Abstract
Prostate cancer (PCa) is a clinically heterogeneous disease. Predicting clinically significant PCa with low-intermediate prostate-specific antigen (PSA), which often includes aggressive cancers, is imperative. This study evaluated the predictive accuracy of deep learning analysis using multimodal medical data focused on clinically significant PCa in patients with PSA ≤ 20 ng/mL. Our cohort study included 178 consecutive patients who underwent ultrasound-guided prostate biopsy. Deep learning analyses were applied to predict clinically significant PCa. We generated receiver operating characteristic curves and calculated the corresponding area under the curve (AUC) to assess the prediction. The AUC of the integrated medical data using our multimodal deep learning approach was 0.878 (95% confidence interval [CI]: 0.772-0.984) in all patients without PSA restriction. Despite the reduced predictive ability of PSA when restricted to PSA ≤ 20 ng/mL (
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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.