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] |
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URL: | https://www.wjgnet.com/1007-9327/full/v27/i33/5610.htm |
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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
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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 chemoradiation. European Radiology 2023; 33(12): 8554 doi: 10.1007/s00330-023-09884-7
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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 Cancer. Journal of Gastrointestinal Cancer 2023; 54(4): 1158 doi: 10.1007/s12029-022-00909-w
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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 Cancers. Cancers 2022; 15(1): 63 doi: 10.3390/cancers15010063
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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 imaging. Journal of Orthopaedic Surgery and Research 2024; 19(1) doi: 10.1186/s13018-024-04569-3
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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 study. World Journal of Gastroenterology 2024; 30(16): 2233-2248 doi: 10.3748/wjg.v30.i16.2233
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Wenzheng Lu, Xiaoying Tan, Yanqi Zhong, Peng Wang, Yuxi Ge, Heng Zhang, Shudong Hu. Spectral CT in the evaluation of perineural invasion status in rectal cancer. Japanese Journal of Radiology 2024; doi: 10.1007/s11604-024-01575-7
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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 radiomics. Journal of Cancer Research and Therapeutics 2023; 19(6): 1552 doi: 10.4103/jcrt.jcrt_2633_22
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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 Cholangiocarcinoma. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.900478
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Xiu-chun Ren, Pan Liang. Analysis of influencing factors of nerve invasion in locally advanced gastric cancer. Abdominal Radiology 2023; 48(9): 3005 doi: 10.1007/s00261-023-03970-6
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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 study. Insights into Imaging 2024; 15(1) doi: 10.1186/s13244-024-01664-1
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