ArticleCancers2022
Breast Tumour Classification Using Ultrasound Elastography with Machine Learning: A Systematic Scoping Review.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis 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.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Computer-aided screening of aspiration risks in dysphagia with wearable technology: a Systematic Review and meta-analysis on test accuracy.Frontiers in bioengineering and biotechnology · 2023Pooled it
- Artificial intelligence-enhanced handheld breast ultrasound for screening: A systematic review of diagnostic test accuracy.PLOS digital health · 2025Article
- Machine learning can reliably predict malignancy of breast lesions based on clinical and ultrasonographic features.Breast cancer research and treatment · 2025Article
- Deep learning approaches for classification tasks in medical X-ray, MRI, and ultrasound images: a scoping review.BMC medical imaging · 2025Article
- Revolutionizing HER-2 assessment: multidimensional radiomics in breast cancer diagnosis.BMC cancer · 2025Article
- Diagnostic value of mammography combined with ultrasound shear wave elastography and magnetic resonance imaging in breast cancer.Oncology letters · 2025Article
- Exploring AI Approaches for Breast Cancer Detection and Diagnosis: A Review Article.Breast cancer (Dove Medical Press) · 2025Review
- Identification of Molecular Subtypes and Prognostic Features of Breast Cancer Based on TGF-β Signaling-related Genes.Cancer informatics · 2025Article
- Ultrasound elastography: advances and challenges in early detection of breast cancer.Frontiers in oncology · 2025Review
- Evaluation of Ex Vivo Shear Wave Elastography of Axillary Sentinel Lymph Nodes in Patients with Early Breast Cancer.Cancers · 2024Article
- CNN-Based Cross-Modality Fusion for Enhanced Breast Cancer Detection Using Mammography and Ultrasound.Tomography (Ann Arbor, Mich.) · 2024Article
- Mathematical Models for Ultrasound Elastography: Recent Advances to Improve Accuracy and Clinical Utility.Bioengineering (Basel, Switzerland) · 2024Review
- A hybrid features fusion-based framework for classification of breast micronodules using ultrasonography.BMC medical imaging · 2024Article
- AI-Powered Synthesis of Structured Multimodal Breast Ultrasound Reports Integrating Radiologist Annotations and Deep Learning Analysis.Bioengineering (Basel, Switzerland) · 2024Article
- Shear-Wave Elastography Gradient Analysis of Newly Diagnosed Breast Tumours: A Critical Analysis.Diagnostics (Basel, Switzerland) · 2024Article
- Ultrasound Elastography Assessment of Knee Intra-Articular Adhesions at Varying Knee Angles.Bioengineering (Basel, Switzerland) · 2024Article
- Single‑cell RNA‑seq necroptosis‑related genes predict the prognosis of breast cancer and affect the differentiation of CD4Molecular and clinical oncology · 2024Article
- A twin convolutional neural network with hybrid binary optimizer for multimodal breast cancer digital image classification.Scientific reports · 2024Article
- U structured network with three encoding paths for breast tumor segmentation.Scientific reports · 2023Article
- Sonoelastography for Testicular Tumor Identification: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy.Cancers · 2023Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Ultrasound elastography can quantify stiffness distribution of tissue lesions and complements conventional B-mode ultrasound for breast cancer screening. Recently, the development of computer-aided diagnosis has improved the reliability of the system, whilst the inception of machine learning, such as deep learning, has further extended its power by facilitating automated segmentation and tumour classification. The objective of this review was to summarize application of the machine learning model to ultrasound elastography systems for breast tumour classification. Review databases included PubMed, Web of Science, CINAHL, and EMBASE. Thirteen (
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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.