ArticleEuropean journal of nuclear medicine and molecular imaging2021
Machine learning-based analysis of [
Article in European journal of nuclear medicine and molecular imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 84 papers, 8 of them syntheses that pooled it.
What it found
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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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
84 citing papers in PubMed, 8 syntheses or guidelines pooled it, 134 citations in OpenAlex.
- The diagnostic value of radiomics-based machine learning for lymph node metastasis in prostate cancer: a systematic review and meta-analysis.Frontiers in oncology · 2026Pooled it
- Artificial Intelligence-Enabled Imaging for Predicting Preoperative Extraprostatic Extension in Prostate Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 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
- Algorithms on the rise: a machine learning-driven survey of prostate cancer literature.Frontiers in oncology · 2025Pooled it
- The predictive value of machine learning and nomograms for lymph node metastasis of prostate cancer: a systematic review and meta-analysis.Prostate cancer and prostatic diseases · 2023Pooled it
- A systematic review and meta-analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck squamous cell carcinoma patients.Cancer medicine · 2023Pooled it
- Radiomics and artificial intelligence in prostate cancer: new tools for molecular hybrid imaging and theragnostics.European radiology experimental · 2022Pooled it
- Radiomics in prostate cancer imaging for a personalized treatment approach - current aspects of methodology and a systematic review on validated studies.Theranostics · 2021Pooled it
- [18F]F-DCFPyL PET/MRI radiomics for intraprostatic prostate cancer detection and metastases prediction using whole-gland segmentation.The British journal of radiology · 2025Trial
- Emerging frontiers and challenges of artificial intelligence in PSMA-PET imaging: pioneering a new chapter in prostate cancer care.Japanese journal of radiology · 2026Review
- Explainable artificial intelligence reveals key surgical parameters in robot-assisted and open radical prostatectomy.Scientific reports · 2026Article
- Artificial intelligence and surgical data science in robot-assisted radical prostatectomy: global research trends, knowledge structure, and emerging frontiers.Journal of robotic surgery · 2026Review
- Article
- [Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Non-invasive diagnosis strategy integrating PSMA PET/CT and mpMRI for patients with suspected prostate cancer: a multi-center study.BMC medicine · 2026Article
- Enhanced prediction of postlaminar optic nerve invasion in retinoblastoma using high-resolution MRI: integrating qualitative imaging features, optic nerve measurements and tumor radiomics.European radiology · 2026Article
- Artificial Intelligence Versus Conventional Methods for NCCN Risk Stratification in Localized Prostate Cancer (2020-2025): A Systematic Review.Prostate cancer · 2026Review
- PSMA PET/CT improves precision diagnosis, treatment, and clinical decision-making in prostate cancer.American journal of translational research · 2026Review
- The Role of Artificial Intelligence in Theranostics.Journal of nuclear medicine technology · 2025Review
- Advancements in artificial intelligence for prostate cancer: Optimizing diagnosis, treatment, and prognostic assessment.Asian journal of urology · 2025Review
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
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeQuantitative prostate-specific membrane antigen (PSMA) PET analysis may provide for non-invasive and objective risk stratification of primary prostate cancer (PCa) patients. We determined the ability of machine learning-based analysis of quantitative [
methodsIn a prospective cohort study, 76 patients with intermediate- to high-risk PCa scheduled for robot-assisted radical prostatectomy with extended pelvic lymph node dissection underwent pre-operative [
resultsThe radiomics-based machine learning models predicted LNI (AUC 0.86 ± 0.15, p < 0.01), nodal or distant metastasis (AUC 0.86 ± 0.14, p < 0.01), Gleason score (0.81 ± 0.16, p < 0.01), and ECE (0.76 ± 0.12, p < 0.01). The highest AUCs reached using standard PET metrics were lower than those of radiomics-based models. For LNI and metastasis prediction, PVC and a higher delineation threshold improved model stability. Machine learning pre-processing methods had a minor impact on model performance.
conclusionMachine learning-based analysis of quantitative [
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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.