X. Meng

发表

Multidisciplinary team consultation for resectable Gastric Cancer: A propensity score matching analysis

Kaikai Wei, Shi Chen, Jian-jun Xiao, 2021, Journal of Cancer.

Clinical Anastomotic Leakage After Rectal Cancer Resection Can Be Predicted by Pelvic Anatomic Features on Preoperative MRI Scans: A Secondary Analysis of a Randomized Controlled Trial.

Lei Wang, W. Cao, Q. Qin, 2019, Diseases of the colon and rectum.

Association of CT-Based Delta Radiomics Biomarker With Progression-Free Survival in Patients With Colorectal Liver Metastases Undergo Chemotherapy

Y. Liao, S. Ye, Ximin Pan, 2022, Frontiers in Oncology.

Intestinal fibrosis classification in patients with Crohn’s disease using CT enterography–based deep learning: comparisons with radiomics and radiologists

Minhu Chen, Yikai Xu, Zi-Ping Li, 2022, European Radiology.

MRI-defined high-risk rectal cancer patients: outcome comparison between neoadjuvant chemoradiotherapy plus TME and TME plus adjuvant chemotherapy or TME alone.

N. Hong, Ziqiang Wang, Yi Wang, 2021, The British journal of radiology.

Mild phototherapy mediated by manganese dioxide-loaded mesoporous polydopamine enhances immunotherapy against colorectal cancer.

X. Shuai, D. Ma, Zecong Xiao, 2022, Biomaterials science.

Terminal Reaches of the Branches from Middle Colic Artery and Their Correlation with Right Colic Artery

W. Cao, J. Zou, Jia Ke, 2022, Indian Journal of Surgery.

Anatomical variations of the branches from left colic artery and middle colic artery at splenic flexure

W. Cao, J. Zou, Jia Ke, 2022, Surgical and Radiologic Anatomy.

Prevalent Pseudoprogression and Pseudoresidue in Patients With Rectal Cancer Treated With Neoadjuvant Immune Checkpoint Inhibitors.

Meijin Huang, Juan Li, Yuanhui Wu, 2023, Journal of the National Comprehensive Cancer Network : JNCCN.

Tumor response as defined by iRECIST in gastrointestinal malignancies treated with PD-1 and PD-L1 inhibitors and correlation with survival

O. Gevaert, Kaikai Wei, Hong Zheng, 2021, BMC Cancer.

A Machine Learning Model for Predicting a Major Response to Neoadjuvant Chemotherapy in Advanced Gastric Cancer

Kaikai Wei, Gang-ping Wang, J. Peng, 2021, Frontiers in Oncology.

Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational study.

M. Hung, Guanyu Yang, Weihua Zhou, 2022, The Lancet. Digital health.

Low Cerebral Glucose Metabolism: A Potential Predictor for the Severity of Vascular Parkinsonism and Parkinson's Disease.

Xiaochun Meng, Jiaping Lin, B. Tang, 2015, Aging and disease.

Deep learning radiomics-based prediction of distant metastasis in patients with locally advanced rectal cancer after neoadjuvant chemoradiotherapy: A multicentre study

Jie Tian, Zhenyu Liu, Zhenchao Tang, 2021, EBioMedicine.

Predicting distant metastasis and chemotherapy benefit in locally advanced rectal cancer

Meiyun Wang, Jie Tian, Jiangang Liu, 2020, Nature Communications.

Intestinal fibrosis classification in patients with Crohn’s disease using CT enterography–based deep learning: comparisons with radiomics and radiologists

Minhu Chen, Yikai Xu, Bingsheng Huang, 2022, European Radiology.

Deep learning–based fully automated detection and segmentation of lymph nodes on multiparametric-mri for rectal cancer: A multicentre study

Xin Gao, Yuguo Tang, Mengmeng Wang, 2020, EBioMedicine.

Radiomic signature-based nomogram to predict disease-free survival in stage II and III colon cancer.

Jie Tian, Zhenyu Liu, N. Hong, 2020, European journal of radiology.

GSH-Responsive Metal-Organic Framework for Intratumoral Release of NO and IDO Inhibitor to Enhance Antitumor Immunotherapy.

X. Shuai, Hong Xiao, Zecong Xiao, 2022, Small.

Quantitative study of liver hemodynamic changes in rats with small-for-size syndrome by the 4D-CT perfusion technique.

Binghui Chen, Kaikai Wei, Jie Ren, 2019, The British journal of radiology.

A new magnetic resonance imaging tumour response grading scheme for locally advanced rectal cancer

Jian Zheng, Xiangbo Wan, P. Xie, 2022, British Journal of Cancer.

Preoperative radiomic signature based on multiparametric magnetic resonance imaging for noninvasive evaluation of biological characteristics in rectal cancer

Xin Gao, Yangchuan Liu, Lei Wang, 2018, European Radiology.

Fully convolutional networks (FCNs)-based segmentation method for colorectal tumors on T2-weighted magnetic resonance images

Xin Gao, Rui Zhang, Xiaodong Wu, 2018, Australasian Physical & Engineering Sciences in Medicine.

A novel ultrasound scanning approach for evaluating femoral cartilage defects of the knee: comparison with routine magnetic resonance imaging

Jie Ren, X. Meng, Jun-yan Cao, 2018, Journal of Orthopaedic Surgery and Research.

A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study

Lei Wu, Zhenwei Shi, J. Ren, 2022, EClinicalMedicine.

Application of liver acquisition with volume acceleration enhanced sequence in improving the accuracy of reassessing organ-invasive rectal mucinous adenocarcinoma after chemoradiation.

D. Ren, Bang Hu, W. Cao, 2020, European journal of radiology.

Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer

Jiancong Hu, P. Lan, Meijin Huang, 2021, Journal of translational medicine.

Fully convolutional networks (FCNs)-based segmentation method for colorectal tumors on T2-weighted magnetic resonance images

W. Xia, Junming Jian, Xin Gao, 2018, Australasian Physical & Engineering Sciences in Medicine.

An MRI Deep Learning Model Predicts Outcome in Rectal Cancer.

Jakob Nikolas Kather, S. Nebelung, D. Truhn, 2023, Radiology.

Full convolutional network based multiple side-output fusion architecture for the segmentation of rectal tumors in magnetic resonance images: A multi-vendor study.

Xin Gao, Mengmeng Wang, Zhao Ran, 2019, Medical physics.