ArticleEuropean journal of nuclear medicine and molecular imaging2023
Role of [
Article in European journal of nuclear medicine and molecular imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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
28 citing papers in PubMed, 35 citations in OpenAlex.
- [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
- Preoperative prediction of Ki-67 expression and prognosis in breast cancer based on contrast-enhanced cone-beam breast CT: a two-centre study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Preoperative assessment of IDH status in adult glioma by integratedEJNMMI research · 2026Article
- Article
- Preoperative prediction of serosal invasion in gastric cancer using multiphase contrast-enhanced CT radiomics.Frontiers in oncology · 2026Article
- Developing an interpretable clinical-radiomics machine learning model using whole transition zone MRI analysis for improving diagnosis of transition zone prostate cancer.Frontiers in oncology · 2026Article
- Deep learning models built from PSMA PET of the primary tumor can predict synchronous and metachronous prostate cancer metastases.PloS one · 2026Article
- The Role of Artificial Intelligence in Theranostics.Journal of nuclear medicine technology · 2025Review
- Machine learning-based construction and validation of an radiomics model for predicting ISUP grading in prostate cancer: a multicenter radiomics study based on [68Ga]Ga-PSMA PET/CT.European journal of nuclear medicine and molecular imaging · 2025Article
- Application value of radiomics features based on PSMA PET/CT in diagnosis of clinically significant prostate cancer: a comparison between manual and automatic segmentation.BMC medical imaging · 2025Article
- Efficacy of PSMA PET/CT radiomics analysis for risk stratification in newly diagnosed prostate cancer: a multicenter study.BMC medical imaging · 2025Article
- Enhanced ISUP grade prediction in prostate cancer using multi-center radiomics data.Abdominal radiology (New York) · 2025Article
- Radiomics Features from Different Prostatic Zones onCancers · 2025Article
- The value of habitat analysis based onBMC medical imaging · 2025Article
- The Role of Radiomics and Artificial Intelligence Applied to Staging PSMA PET in Assessing Prostate Cancer Aggressiveness.Journal of clinical medicine · 2025Review
- Exploring the role of multimodal [European journal of nuclear medicine and molecular imaging · 2025Article
- End-to-end [Abdominal radiology (New York) · 2025Article
- Significance of multi-task deep learning neural networks for diagnosing clinically significant prostate cancer in plain abdominal CT.Frontiers in oncology · 2025Article
- Machine-Learning Based Computed Tomography Radiomics Nomgram For Predicting Perineural Invasion In Gastric Cancer.Current medical imaging · 2025Article
Corrections and comments
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Authors and funding
18 authors at 2 institutions in 1 country.
Funding
Abstract
purposeThe aim of this study is to investigate the role of [
methodsThis retrospective study included 47 PCa patients who underwent [
resultsISUP grade at biopsy was upgraded in 9/47 patients after prostatectomy, resulting in a bACC = 85.9%, SN = 71.9%, SP = 100%, PPV = 100%, and NPV = 62.5%, while the best-performing radiomic model yielded a bACC = 87.6%, SN = 88.6%, SP = 86.7%, PPV = 94%, and NPV = 82.5%. All radiomic models trained with at least 2 RFs (GLSZM-Zone Entropy and Shape-Least Axis Length) outperformed the control models. Conversely, no significant differences were found for radiomic models trained with 2 or more RFs (Mann-Whitney p > 0.05).
conclusionThese findings support the role of [
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.