Sina Wang

Guangzhou, China

Last Updated: 09/26/2026

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Found 10 publications

Enhancing Specificity in Predicting Axillary Lymph Node Metastasis in Breast Cancer through an Interpretable Machine Learning Model with CEM and Ultrasound Integration.

Enhancing Specificity in Predicting Axillary Lymph Node Metastasis in Breast Cancer through an Interpretable Machine Learning Model with CEM and Ultrasound Integration.

Journal: Technology in cancer research & treatment

Published: April 17, 2025

Differentiation Between Phyllodes Tumor and Fibroadenoma of the Breast: A Radiomics Prediction Model Based on Full-Field Digital Mammography & Digital Tomosynthesis.

Differentiation Between Phyllodes Tumor and Fibroadenoma of the Breast: A Radiomics Prediction Model Based on Full-Field Digital Mammography & Digital Tomosynthesis.

Journal: Technology in cancer research & treatment

Published: October 08, 2024

Unlocking the Potential of Training: Enhancing Inter-reader Agreement in Background Parenchymal Enhancement Assessment.

Unlocking the Potential of Training: Enhancing Inter-reader Agreement in Background Parenchymal Enhancement Assessment.

Journal: The British journal of radiology

Published: July 24, 2024

Addition of contrast-enhanced mammography enhancement patterns and morphology for differentiating benign from malignant papillary breast lesions.

Addition of contrast-enhanced mammography enhancement patterns and morphology for differentiating benign from malignant papillary breast lesions.

Journal: The British journal of radiology

Published: June 09, 2024

Breast masses with rim enhancement on contrast-enhanced mammography: morphological and enhancement features for diagnosis and differentiation of benign and malignant.

Breast masses with rim enhancement on contrast-enhanced mammography: morphological and enhancement features for diagnosis and differentiation of benign and malignant.

Journal: The British journal of radiology

Published: September 03, 2023

Contrast-enhanced mammography-based interpretable machine learning model for the prediction of the molecular subtype breast cancers.

Contrast-enhanced mammography-based interpretable machine learning model for the prediction of the molecular subtype breast cancers.

Journal: BMC medical imaging

Published: May 09, 2023

Atypical architectural distortion detection in digital breast tomosynthesis: a computer-aided detection model with adaptive receptive field.

Atypical architectural distortion detection in digital breast tomosynthesis: a computer-aided detection model with adaptive receptive field.

Journal: Physics in medicine and biology

Published: March 08, 2022

Can a Computer-Aided Mass Diagnosis Model Based on Perceptive Features Learned From Quantitative Mammography Radiology Reports Improve Junior Radiologists' Diagnosis Performance? An Observer Study.

Can a Computer-Aided Mass Diagnosis Model Based on Perceptive Features Learned From Quantitative Mammography Radiology Reports Improve Junior Radiologists' Diagnosis Performance? An Observer Study.

Journal: Frontiers in oncology

Published: September 09, 2021

The diagnostic value of chest X-ray in coronavirus disease 2019: A comparative study of X-ray and CT.

The diagnostic value of chest X-ray in coronavirus disease 2019: A comparative study of X-ray and CT.

Journal: Science progress

Published: August 23, 2021

Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms.

Predicting the molecular subtype of breast cancer and identifying interpretable imaging features using machine learning algorithms.

Journal: European radiology

Published: June 25, 2021

Showing 1-10 of 10

Last Updated: 09/26/2026