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Diseases of the Colon and Rectum|September 8, 2023
A Longitudinal MRI-Based Artificial Intelligence System to Predict Pathological Complete Response After Neoadjuvant Therapy in Rectal Cancer: A Multicenter Validation StudyJia Ke, Cheng Jin, Jinghua Tang, et al.European Radiology|November 11, 2018
Preoperative radiomic signature based on multiparametric magnetic resonance imaging for noninvasive evaluation of biological characteristics in rectal cancerXiaochun Meng, Wei Xia, Peiyi Xie, et al.Aging and Disease|December 1, 2015
Low Cerebral Glucose Metabolism: A Potential Predictor for the Severity of Vascular Parkinsonism and Parkinson's DiseaseYunqi Xu, Xiaobo Wei, Xu Liu, et al.Medical Image Analysis|July 3, 2022
Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical imagesFeng Gao, Minhao Hu, Min-Er Zhong, et al.Ebiomedicine|June 9, 2020
Deep learning-based fully automated detection and segmentation of lymph nodes on multiparametric-mri for rectal cancer: A multicentre studyXingyu Zhao, Peiyi Xie, Mengmeng Wang, et al.European Journal of Radiology|August 3, 2021
Radiomics diagnosed histopathological growth pattern in prediction of response and 1-year progression free survival for colorectal liver metastases patients treated with bevacizumab containing chemotherapyShengcai Wei, Yuqi Han, Hanjiang Zeng, et al.Journal of the National Comprehensive Cancer Network : JNCCN|February 15, 2023
Prevalent Pseudoprogression and Pseudoresidue in Patients With Rectal Cancer Treated With Neoadjuvant Immune Checkpoint InhibitorsYumo Xie, Jinxin Lin, Ning Zhang, et al.European Radiology|May 26, 2022
Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologistsJixin Meng, Zixin Luo, Zhihui Chen, et al.The Lancet. Digital Health|December 25, 2021
Development and validation of a radiopathomics model to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a multicentre observational studyLili Feng, Zhenyu Liu, Chaofeng Li, et al.Pageof 6