ArticleDiagnostics (Basel, Switzerland)2022
Freely Available, Fully Automated AI-Based Analysis of Primary Tumour and Metastases of Prostate Cancer in Whole-Body [
Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 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
- Deep learning-based PSMA PET segmentation repeatability: A post-hoc analysis of a single-center, prospective, test-retest trial.La Radiologia medica · 2026Trial
- Deep learning for automatic detection of prostatectomy in CT images of prostate cancer patients.Physical and engineering sciences in medicine · 2026Article
- coPERCIST: AI-assisted PET-CT response assessment.European journal of nuclear medicine and molecular imaging · 2026Article
- Context-level machine learning to improve the identification of lymph node and bone metastases in prostate cancer patients using [EJNMMI physics · 2025Article
- Lymph node disease in 2-deoxy-2-fluorodeoxyglucose positron emission tomography/computed tomography imaging: Advances in artificial intelligence-driven automatic segmentation and precise diagnosis.World journal of clinical oncology · 2025Review
- A fully automated AI-based method for tumour detection and quantification on [EJNMMI physics · 2025Article
- AI based automatic measurement of split renal function in [EJNMMI reports · 2025Article
- PSMA PET/CT for prostate cancer diagnosis: current applications and future directions.Journal of cancer research and clinical oncology · 2025Review
- Artificial Intelligence and Radiomics Applied to Prostate Cancer Bone Metastasis Imaging: A Review.iRadiology · 2024Article
- Catalyzing Precision Medicine: Artificial Intelligence Advancements in Prostate Cancer Diagnosis and Management.Cancers · 2024Review
- The Application of Radiomics and AI to Molecular Imaging for Prostate Cancer.Journal of personalized medicine · 2024Review
- A Systematic Review on Artificial Intelligence Evaluating Metastatic Prostatic Cancer and Lymph Nodes on PSMA PET Scans.Cancers · 2024Review
- Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens.Diagnostics (Basel, Switzerland) · 2024Review
- Can Machine Learning Models Detect and Predict Lymph Node Involvement in Prostate Cancer? A Comprehensive Systematic Review.Journal of clinical medicine · 2023Review
- AI-based quantification of whole-body tumour burden on somatostatin receptor PET/CT.European journal of hybrid imaging · 2023Article
- Automated quantification of PET/CT skeletal tumor burden in prostate cancer using artificial intelligence: The PET index.European journal of nuclear medicine and molecular imaging · 2023Article
- Deep learning image segmentation approaches for malignant bone lesions: a systematic review and meta-analysis.Frontiers in radiology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 4 institutions in 1 country.
Funding
Abstract
Here, we aimed to develop and validate a fully automated artificial intelligence (AI)-based method for the detection and quantification of suspected prostate tumour/local recurrence, lymph node metastases, and bone metastases from [
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.