ArticleFrontiers in oncology2019
Detection of Dominant Intra-prostatic Lesions in Patients With Prostate Cancer Using an Artificial Neural Network and MR Multi-modal Radiomics Analysis.
Article in Frontiers in oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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
18 citing papers in PubMed.
- Machine learning-DeepSurv prediction model integrating mpMRI radiomics and genomic biomarkers for BCR-free survival and tumor response in prostate radiotherapy.Journal of radiation research · 2026Article
- Detecting MRI-Invisible Prostate Cancers Using a Weakly Supervised Deep Learning Model.International journal of biomedical imaging · 2024Article
- MRI-derived radiomics models for diagnosis, aggressiveness, and prognosis evaluation in prostate cancer.Journal of Zhejiang University. Science. B · 2023Review
- Deep learning-based dominant index lesion segmentation for MR-guided radiation therapy of prostate cancer.Medical physics · 2023Article
- Radiomics in colorectal cancer patients.World journal of gastroenterology · 2023Review
- Radiomics-based intracranial thrombus features on preoperative noncontrast CT predicts successful recanalization of mechanical thrombectomy in acute ischemic stroke.Quantitative imaging in medicine and surgery · 2023Article
- Virtual biopsy in abdominal pathology: where do we stand?BJR open · 2023Review
- Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses.IEEE open journal of engineering in medicine and biology · 2023Article
- Ultra high speed SPECT bone imaging enabled by a deep learning enhancement method: a proof of concept.EJNMMI physics · 2022Article
- Evaluation of the Efficiency of MRI-Based Radiomics Classifiers in the Diagnosis of Prostate Lesions.Frontiers in oncology · 2022Article
- Prostate Cancer Radiogenomics-From Imaging to Molecular Characterization.International journal of molecular sciences · 2021Review
- Artificial Intelligence Based Algorithms for Prostate Cancer Classification and Detection on Magnetic Resonance Imaging: A Narrative Review.Diagnostics (Basel, Switzerland) · 2021Review
- Simultaneous Identification ofCancers · 2021Article
- Differentiating Between Multiple Myeloma and Metastasis Subtypes of Lumbar Vertebra Lesions Using Machine Learning-Based Radiomics.Frontiers in oncology · 2021Article
- Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms.Journal of oncology · 2021Review
- Article
- MRI-Derived Radiomics to Guide Post-operative Management for High-Risk Prostate Cancer.Frontiers in oncology · 2019Article
- Radiomics in prostate cancer: an up-to-date review.Therapeutic advances in urologyReview
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.