Beibei Jiang

100 Haining Rd
Shanghai, 200080, China

Last Updated: 09/26/2026

Save publications for later

Sign Up

Not sure about your diagnosis?

Check Your Symptoms

Found 17 publications

Measurement Accuracy and Repeatability of RECIST-Defined Pulmonary Lesions and Lymph Nodes in Ultra-Low-Dose CT Based on Deep Learning Image Reconstruction.

Measurement Accuracy and Repeatability of RECIST-Defined Pulmonary Lesions and Lymph Nodes in Ultra-Low-Dose CT Based on Deep Learning Image Reconstruction.

Journal: Cancers

Published: July 25, 2022

Clinical application of deep learning and radiomics in hepatic disease imaging: a systematic scoping review.

Clinical application of deep learning and radiomics in hepatic disease imaging: a systematic scoping review.

Journal: The British journal of radiology

Published: July 11, 2022

Machine-learning-based radiomics identifies atrial fibrillation on the epicardial fat in contrast-enhanced and non-enhanced chest CT.

Machine-learning-based radiomics identifies atrial fibrillation on the epicardial fat in contrast-enhanced and non-enhanced chest CT.

Journal: The British journal of radiology

Published: March 31, 2022

COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images.

COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images.

Journal: The British journal of radiology

Published: February 10, 2022

Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.

Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.

Journal: Radiology

Published: January 18, 2022

Motion artifact removal in coronary CT angiography based on generative adversarial networks.

Motion artifact removal in coronary CT angiography based on generative adversarial networks.

Journal: European radiology

Published: January 13, 2022

Development and multicenter validation of chest X-ray radiography interpretations based on natural language processing.

Development and multicenter validation of chest X-ray radiography interpretations based on natural language processing.

Journal: Communications medicine

Published: May 28, 2021

Machine-Learning-Derived Nomogram Based on 3D Radiomic Features and Clinical Factors Predicts Progression-Free Survival in Lung Adenocarcinoma.

Machine-Learning-Derived Nomogram Based on 3D Radiomic Features and Clinical Factors Predicts Progression-Free Survival in Lung Adenocarcinoma.

Journal: Frontiers in oncology

Published: April 08, 2021

Development of artificial intelligence in epicardial and pericoronary adipose tissue imaging: a systematic review.

Development of artificial intelligence in epicardial and pericoronary adipose tissue imaging: a systematic review.

Journal: European journal of hybrid imaging

Published: March 20, 2021

Simultaneous Identification of EGFR,KRAS,ERBB2, and TP53 Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics.

Simultaneous Identification of EGFR,KRAS,ERBB2, and TP53 Mutations in Patients with Non-Small Cell Lung Cancer by Machine Learning-Derived Three-Dimensional Radiomics.

Journal: Cancers

Published: March 02, 2021

Lung Nodule Detectability of Artificial Intelligence-assisted CT Image Reading in Lung Cancer Screening.

Lung Nodule Detectability of Artificial Intelligence-assisted CT Image Reading in Lung Cancer Screening.

Journal: Current medical imaging

Published: March 01, 2021

Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors.

Classification of moving coronary calcified plaques based on motion artifacts using convolutional neural networks: a robotic simulating study on influential factors.

Journal: BMC medical imaging

Published: December 15, 2020

Showing 1-12 of 17

Last Updated: 09/26/2026