ArticleFrontiers in oncology2020
Deep Learning vs. Radiomics for Predicting Axillary Lymph Node Metastasis of Breast Cancer Using Ultrasound Images: Don't Forget the Peritumoral Region.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 142 papers, 7 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
142 citing papers in PubMed, 7 syntheses or guidelines pooled it, 258 citations in OpenAlex.
- Assessing the performance of deep learning and hand-crafted radiomics models using MRI and ultrasound in predicting axillary lymph node status in breast cancer: a systematic review and meta-analysis.European radiology · 2026Pooled it
- Accuracy of Deep Learning for Detecting Axillary Lymph Node Metastasis in Breast Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- The predictive value of multiple artificial intelligence models in axillary lymph node metastasis of breast cancer detected by ultrasound - a network meta-analysis.Frontiers in oncology · 2026Pooled it
- Prediction of sentinel lymph node status in patients with early breast cancer using breast imaging as an alternative to surgical staging-a systematic review and meta-analysis.Systematic reviews · 2025Pooled it
- Quality and accuracy of radiomics models in predicting KRAS status in lung cancer: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
- Bibliometric and visual analysis of radiomics for evaluating lymph node status in oncology.Frontiers in medicine · 2024Pooled it
- Diagnostic performance of radiomics in predicting axillary lymph node metastasis in breast cancer: A systematic review and meta-analysis.Frontiers in oncology · 2022Pooled it
- Development and validation of MRI-based deep learning models for prediction of microsatellite instability in rectal cancer.Cancer medicine · 2021Trial
- Peritumoral ultrasound-driven multimodal AI model for predicting lymphovascular space invasion and prognosis in cervical cancer.Abdominal radiology (New York) · 2026Article
- Article
- A multimodal deep learning classifier for prediction of HER2-low expression in triple-negative breast cancer.BMC medical imaging · 2026Article
- Development and validation of intratumoral and peritumoral CT-based radiomics nomograms for predicting malignancy and invasiveness of pulmonary ground-glass nodules: a retrospective study.Quantitative imaging in medicine and surgery · 2026Article
- Integrating intratumoral and peritumoral ultrasound radiomics with clinicopathological features to predict axillary lymph node metastasis in early breast cancer.Gland surgery · 2026Article
- AI-assisted radiomics for classification of benign and non-benign right heart masses in 2D-echocardiography.Journal of translational medicine · 2026Article
- Predicting axillary lymph node metastasis in breast cancer via quantitative analysis of VueBox ultrasound contrast-enhanced imaging combined with multimodal feature fusion.Quantitative imaging in medicine and surgery · 2026Article
- Nomogram combining ultrasound radiomics and clinical factors for predicting placenta accreta spectrum in patients with placenta previa: a two-center study.BMC medical imaging · 2026Article
- Ensemble-based high-performance deep learning models for medical image retrieval in breast cancer detection.Scientific reports · 2026Article
- Comparison of CT-based radiomics models for the prediction of human epidermal growth factor receptor 2 status in gastric cancer.BMC medical imaging · 2026Article
- Artificial Intelligence in Triple-Negative Breast Cancer: Applications in Diagnosis, Treatment Response, and Prognosis.Diagnostics (Basel, Switzerland) · 2026Review
- Stratified prediction of HER2 status in breast cancer by integrating intratumoral and peritumoral radiomics from DCE-MRI.BMC cancer · 2026Article
82 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
8 authors at 3 institutions in 1 country.
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.