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Cited by in CrossRef
For: Li M, Jin YM, Zhang YC, Zhao YL, Huang CC, Liu SM, Song B. Radiomics for predicting perineural invasion status in rectal cancer. World J Gastroenterol 2021; 27(33): 5610-5621 [PMID: 34588755 DOI: 10.3748/wjg.v27.i33.5610]
URL: https://www.wjgnet.com/1007-9327/full/v27/i33/5610.htm
Number Citing Articles
1
Mo Zheng, Shouliang Miao, Dan Chen, Fei Yao, Qinqin Xiao, Guanxia Zhu, Chenqiang Pan, Tao Lei, Chenhao Ye, Yunjun Yang, Lusi Ye. Can radiomics replace the SPARCC scoring system in evaluating bone marrow edema of sacroiliac joints in patients with axial spondyloarthritis?Clinical Rheumatology 2023; 42(6): 1675 doi: 10.1007/s10067-023-06543-6
2
Jin Wang, Xiang Zhu, Jian Zeng, Cheng Liu, Wei Shen, Xiaojiang Sun, Qingren Lin, Jun Fang, Qixun Chen, Yongling Ji. Using clinical and radiomic feature–based machine learning models to predict pathological complete response in patients with esophageal squamous cell carcinoma receiving neoadjuvant chemoradiationEuropean Radiology 2023; 33(12): 8554 doi: 10.1007/s00330-023-09884-7
3
Joao Miranda, Natally Horvat, Jose A. B. Araujo-Filho, Kamila S. Albuquerque, Charlotte Charbel, Bruno M. C. Trindade, Daniel L. Cardoso, Lucas de Padua Gomes de Farias, Jayasree Chakraborty, Cesar Higa Nomura. The Role of Radiomics in Rectal CancerJournal of Gastrointestinal Cancer 2023; 54(4): 1158 doi: 10.1007/s12029-022-00909-w
4
Azadeh Tabari, Shin Mei Chan, Omar Mustafa Fathy Omar, Shams I. Iqbal, Michael S. Gee, Dania Daye. Role of Machine Learning in Precision Oncology: Applications in Gastrointestinal CancersCancers 2022; 15(1): 63 doi: 10.3390/cancers15010063
5
Wen-xi Liu, Hong Wu, Chi Cai, Qing-quan Lai, Yi Wang, Yuan-zhe Li. Research on automatic recognition radiomics algorithm for early sacroiliac arthritis based on sacroiliac MRI imagingJournal of Orthopaedic Surgery and Research 2024; 19(1) doi: 10.1186/s13018-024-04569-3
6
Yan Liu, Bai-Jin-Tao Sun, Chuan Zhang, Bing Li, Xiao-Xuan Yu, Yong Du. Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model: A dual-center studyWorld Journal of Gastroenterology 2024; 30(16): 2233-2248 doi: 10.3748/wjg.v30.i16.2233
7
Qiaoling Chen, Yanfen Cui, Ting Xue, Hui Peng, Manman Li, Xinghua Zhu, Shaofeng Duan, Hongmei Gu, Feng Feng. Computed tomography-based radiomics nomogram for the preoperative prediction of perineural invasion in colorectal cancer: a multicentre studyAbdominal Radiology 2022; 47(9): 3251 doi: 10.1007/s00261-022-03620-3
8
Bo Deng, Qian Wang, Yuanqing Liu, Yanwei Yang, Xiaolong Gao, Hui Dai. A nomogram based on MRI radiomics features of mesorectal fat for diagnosing T2- and T3-stage rectal cancerAbdominal Radiology 2024;  doi: 10.1007/s00261-023-04164-w
9
Siyuan Qin, Siyi Lu, Ke Liu, Yan Zhou, Qizheng Wang, Yongye Chen, Enlong Zhang, Hao Wang, Ning Lang. Radiomics from Mesorectal Blood Vessels and Lymph Nodes: A Novel Prognostic Predictor for Rectal Cancer with Neoadjuvant TherapyDiagnostics 2023; 13(12): 1987 doi: 10.3390/diagnostics13121987
10
Jacobo Porto-Álvarez, Gary T. Barnes, Alex Villanueva, Roberto García-Figueiras, Sandra Baleato-González, Emilio Huelga Zapico, Miguel Souto-Bayarri. Digital Medical X-ray Imaging, CAD in Lung Cancer and Radiomics in Colorectal Cancer: Past, Present and FutureApplied Sciences 2023; 13(4): 2218 doi: 10.3390/app13042218
11
Jiaxuan Liu, Lingling Sun, Xiang Zhao, Xi Lu. Development and validation of a combined nomogram for predicting perineural invasion status in rectal cancer via computed tomography-based radiomicsJournal of Cancer Research and Therapeutics 2023; 19(6): 1552 doi: 10.4103/jcrt.jcrt_2633_22
12
Peng-Chao Zhan, Pei-jie Lyu, Zhen Li, Xing Liu, Hui-Xia Wang, Na-Na Liu, Yuyuan Zhang, Wenpeng Huang, Yan Chen, Jian-bo Gao. CT-Based Radiomics Analysis for Noninvasive Prediction of Perineural Invasion of Perihilar CholangiocarcinomaFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.900478
13
Margherita Mottola, Rita Golfieri, Alessandro Bevilacqua. The Effectiveness of an Adaptive Method to Analyse the Transition between Tumour and Peritumour for Answering Two Clinical Questions in Cancer ImagingSensors 2024; 24(4): 1156 doi: 10.3390/s24041156
14
Xiu-chun Ren, Pan Liang. Analysis of influencing factors of nerve invasion in locally advanced gastric cancerAbdominal Radiology 2023; 48(9): 3005 doi: 10.1007/s00261-023-03970-6
15
Nian-jun Liu, Mao-sen Liu, Wei Tian, Ya-nan Zhai, Wei-long Lv, Tong Wang, Shun-Lin Guo. The value of machine learning based on CT radiomics in the preoperative identification of peripheral nerve invasion in colorectal cancer: a two-center studyInsights into Imaging 2024; 15(1) doi: 10.1186/s13244-024-01664-1