Changsi Jiang
Shenzhen, 518020, China
Last Updated: 09/26/2026
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Found 12 publications
Construction and validation of a CT-based radiomics-deep learning signature for non-invasive prediction of PD-L1 expression and immunotherapy outcomes in non-small cell lung cancer.
Journal: Translational lung cancer research
Published: December 12, 2025
Multiparametric MRI approach identifies pathologic complete response in patients with local advanced rectal cancer after neoadjuvant therapy.
Journal: BMC medical imaging
Published: September 29, 2025
A SHAP-interpretable XGBoost model: MRI-based intratumoral perfusion heterogeneity predicts HER2-zero, -low, and -positive ternary expression status in breast cancer.
Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
Published: March 19, 2025
Mr-based radiomics analysis of intra-tumor heterogeneity for early treatment response prediction in locally advanced cervical cancer treated with concurrent chemoradiotherapy.
Journal: European journal of radiology
Published: February 15, 2025
CT-Based Super-Resolution Deep Learning Models with Attention Mechanisms for Predicting Spread Through Air Spaces of Solid or Part-Solid Lung Adenocarcinoma.
Journal: Academic radiology
Published: November 07, 2023
Habitat-based radiomics enhances the ability to predict lymphovascular space invasion in cervical cancer: a multi-center study.
Journal: Frontiers in oncology
Published: July 03, 2023
CT-based radiomic phenotypes of lung adenocarcinoma: a preliminary comparative analysis with targeted next-generation sequencing.
Journal: Frontiers in medicine
Published: March 21, 2023
CT-based radiomics signature to predict CD8+ tumor infiltrating lymphocytes in non-small-cell lung cancer.
Journal: Acta radiologica (Stockholm, Sweden : 1987)
Published: September 19, 2022
Development and validation of a CT-based nomogram to predict spread through air space (STAS) in peripheral stage IA lung adenocarcinoma.
Journal: Japanese journal of radiology
Published: October 19, 2021
A CT-based logistic regression model to predict spread through air space in lung adenocarcinoma.
Journal: Quantitative imaging in medicine and surgery
Published: October 05, 2020
CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.
Journal: European radiology
Published: October 13, 2019
Showing 1-12 of 12
Last Updated: 09/26/2026