ArticleDiagnostics (Basel, Switzerland)2020
Color Doppler Ultrasound Improves Machine Learning Diagnosis of Breast Cancer.
Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 50 citations in OpenAlex.
- A Systematic Review and Meta-analysis of Two-Dimensional Breast Ultrasound Radiomics: Implications for Lesion Characterization and Diagnostic Accuracy.Journal of imaging informatics in medicine · 2026Review
- HyFusion-X: hybrid deep and traditional feature fusion with ensemble classifiers for breast cancer detection using mammogram and ultrasound images.Scientific reports · 2025Article
- Deep learning-powered multi-parametric ultrasound for classifying metastatic versus reactive axillary lymph nodes.Breast cancer research : BCR · 2025Article
- Machine learning-based diagnostic and prognostic models for breast cancer: a new frontier on the clinical application of natural killer cell-related gene signatures in precision medicine.Frontiers in immunology · 2025Article
- Ultrasound-based radiomics for the evaluation of breast cancer.Frontiers in oncology · 2025Review
- An updated overview of radiomics-based artificial intelligence (AI) methods in breast cancer screening and diagnosis.Radiological physics and technology · 2024Review
- A preliminary study on the diagnostic value of contrast-enhanced ultrasound and micro-flow imaging for detecting blood flow signals in breast cancer patients.Gland surgery · 2024Article
- Machine learning and new insights for breast cancer diagnosis.The Journal of international medical research · 2024Review
- Automated breast tumor ultrasound image segmentation with hybrid UNet and classification using fine-tuned CNN model.Heliyon · 2023Article
- Breast Cancer Classification Depends on the Dynamic Dipper Throated Optimization Algorithm.Biomimetics (Basel, Switzerland) · 2023Article
- Hydralazine-augmented contrast ultrasound imaging improves the detection of hepatocellular carcinoma.Medical physics · 2023Article
- Prediction of the Malignancy of a Breast Lesion Detected on Breast Ultrasound: Radiomics Applied to Clinical Practice.Cancers · 2023Article
- A non-invasive method for prediction of neurodegenerative diseases using gait signal features.Procedia computer science · 2023Article
- An integrated deep learning model for the prediction of pathological complete response to neoadjuvant chemotherapy with serial ultrasonography in breast cancer patients: a multicentre, retrospective study.Breast cancer research : BCR · 2022Article
- Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion.Sensors (Basel, Switzerland) · 2022Article
- Ultrasound super-resolution imaging for differential diagnosis of breast masses.Frontiers in oncology · 2022Article
- Ultrasound radiomics in personalized breast management: Current status and future prospects.Frontiers in oncology · 2022Review
- Artificial intelligence in medical ultrasonography: driving on an unpaved road.Ultrasonography (Seoul, Korea) · 2021Article
- Combination of color Doppler ultrasound and CT for diagnosing breast cancer.American journal of translational research · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Color Doppler is used in the clinic for visually assessing the vascularity of breast masses on ultrasound, to aid in determining the likelihood of malignancy. In this study, quantitative color Doppler radiomics features were algorithmically extracted from breast sonograms for machine learning, producing a diagnostic model for breast cancer with higher performance than models based on grayscale and clinical category from the Breast Imaging Reporting and Data System for ultrasound (BI-RADS
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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.