For: | Cannella R, La Grutta L, Midiri M, Bartolotta TV. New advances in radiomics of gastrointestinal stromal tumors. World J Gastroenterol 2020; 26(32): 4729-4738 [PMID: 32921953 DOI: 10.3748/wjg.v26.i32.4729] |
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URL: | https://www.wjgnet.com/1948-5190/full/v26/i32/4729.htm |
Number | Citing Articles |
1 |
Giorgia Porrello, Roberto Cannella, Eduardo Alvarez-Hornia Pérez, Giuseppe Brancatelli, Federica Vernuccio. The Neoplastic Side of the Abdominal Wall: A Comprehensive Pictorial Essay of Benign and Malignant Neoplasms. Diagnostics 2023; 13(2): 315 doi: 10.3390/diagnostics13020315
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2 |
Gabriele Tonni, Andrea Palicelli, Maria Bassi, Federica Torricelli, Ilaria Vacca, Lorenzo Aguzzoli, Vincenzo Mandato. Gastrointestinal Stromal Tumors (GISTs) Mimicking Primary Ovarian Tumors or Metastasizing to the Ovaries: A Systematic Literature Review. Cancers 2024; 16(13): 2305 doi: 10.3390/cancers16132305
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3 |
Jiashi Cao, Qiong Li, Huili Zhang, Yanyan Wu, Xiang Wang, Saisai Ding, Song Chen, Shaochun Xu, Guangwen Duan, Defu Qiu, Jiuyi Sun, Jun Shi, Shiyuan Liu. Radiomics model based on MRI to differentiate spinal multiple myeloma from metastases: A two-center study. Journal of Bone Oncology 2024; 45: 100599 doi: 10.1016/j.jbo.2024.100599
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4 |
Boyang Sun, Jingang Liu, Silu Li, Jonathan F. Lovell, Yumiao Zhang. Imaging of Gastrointestinal Tract Ailments. Journal of Imaging 2023; 9(6): 115 doi: 10.3390/jimaging9060115
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5 |
Jian Wang, Meihua Shao, Hongjie Hu, Wenbo Xiao, Guohua Cheng, Guangzhao Yang, Hongli Ji, Susu Yu, Jie Wan, Zongyu Xie, Maosheng Xu. Convolutional neural network applied to preoperative venous-phase CT images predicts risk category in patients with gastric gastrointestinal stromal tumors. BMC Cancer 2024; 24(1) doi: 10.1186/s12885-024-11962-y
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6 |
Giuseppe Cutaia, Rosalia Gargano, Roberto Cannella, Nicoletta Feo, Antonio Greco, Giuseppe Merennino, Nicola Nicastro, Albert Comelli, Viviana Benfante, Giuseppe Salvaggio, Antonio Lo Casto. Image Analysis and Processing. ICIAP 2022 Workshops. Lecture Notes in Computer Science 2022; 13373: 317 doi: 10.1007/978-3-031-13321-3_28
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7 |
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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8 |
Viviana Benfante, Giuseppe Salvaggio, Muhammad Ali, Giuseppe Cutaia, Leonardo Salvaggio, Sergio Salerno, Gabriele Busè, Gabriele Tulone, Nicola Pavan, Domenico Di Raimondo, Antonino Tuttolomondo, Alchiede Simonato, Albert Comelli. Image Analysis and Processing - ICIAP 2023 Workshops. Lecture Notes in Computer Science 2024; 14366: 93 doi: 10.1007/978-3-031-51026-7_9
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9 |
Meihua Shao, Zhongfeng Niu, Linyang He, Zhaoxing Fang, Jie He, Zongyu Xie, Guohua Cheng, Jian Wang. Building Radiomics Models Based on Triple-Phase CT Images Combining Clinical Features for Discriminating the Risk Rating in Gastrointestinal Stromal Tumors. Frontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.737302
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10 |
Tommaso Vincenzo Bartolotta, Adele Taibbi, Angelo Randazzo, Cesare Gagliardo. New frontiers in liver ultrasound: From mono to multi parametricity. World Journal of Gastrointestinal Oncology 2021; 13(10): 1302-1316 doi: 10.4251/wjgo.v13.i10.1302
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11 |
Xianqun Ji, Yu Shang, Lin Tan, Yan Hu, Junjie Liu, Lina Song, Junyan Zhang, Jingxian Wang, Yingjian Ye, Haidong Zhang, Tianfang Peng, Peng An. Prediction of High-Risk Gastrointestinal Stromal Tumor Recurrence Based on Delta-CT Radiomics Modeling: A 3-Year Follow-up Study After Surgery. Clinical Medicine Insights: Oncology 2024; 18 doi: 10.1177/11795549241245698
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12 |
Maxime Barat, Anna Pellat, Anthony Dohan, Christine Hoeffel, Romain Coriat, Philippe Soyer. CT and MRI of Gastrointestinal Stromal Tumours: New Trends and Perspectives. Canadian Association of Radiologists Journal 2024; 75(1): 107 doi: 10.1177/08465371231180510
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13 |
Giovanni Pasini, Alessandro Stefano, Giorgio Russo, Albert Comelli, Franco Marinozzi, Fabiano Bini. Phenotyping the Histopathological Subtypes of Non-Small-Cell Lung Carcinoma: How Beneficial Is Radiomics?. Diagnostics 2023; 13(6): 1167 doi: 10.3390/diagnostics13061167
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14 |
Francesca Giudice, Sergio Salerno, Giuseppe Badalamenti, Gianluca Muto, Antonio Pinto, Massimo Galia, Francesco Prinzi, Salvatore Vitabile, Giuseppe Lo Re. Gastrointestinal Stromal Tumors: Diagnosis, Follow-up and Role of Radiomics in a Single Center Experience. Seminars in Ultrasound, CT and MRI 2023; 44(3): 194 doi: 10.1053/j.sult.2023.03.005
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15 |
Ilaria Canfora, Giuseppe Cutaia, Marco Marcianò, Mauro Calamia, Roberta Faraone, Roberto Cannella, Viviana Benfante, Albert Comelli, Giovanni Guercio, Lo Re Giuseppe, Giuseppe Salvaggio. Image Analysis and Processing. ICIAP 2022 Workshops. Lecture Notes in Computer Science 2022; 13373: 431 doi: 10.1007/978-3-031-13321-3_38
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16 |
Akitoshi Inoue, Shinichi Ota, Michio Yamasaki, Bolorkhand Batsaikhan, Akira Furukawa, Yoshiyuki Watanabe. Gastrointestinal stromal tumors: a comprehensive radiological review. Japanese Journal of Radiology 2022; 40(11): 1105 doi: 10.1007/s11604-022-01305-x
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17 |
Xian‐Da Zhang, Ling Zhang, Ting‐Ting Gong, Zhuo‐Ran Wang, Kang‐Li Guo, Jun Li, Yuan Chen, Jian‐Tao Zhang, Ben‐Gong Ye, Jin Ding, Jian‐Wei Zhu, Feng Liu, Duan‐Min Hu, JianGang Chen, Chun‐Hua Zhou, Duo‐Wu Zou. A combined radiomic model distinguishing GISTs from leiomyomas and schwannomas in the stomach based on endoscopic ultrasonography images. Journal of Applied Clinical Medical Physics 2023; 24(7) doi: 10.1002/acm2.14023
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18 |
Yun Wang, Yurui Wang, Jialiang Ren, Linyi Jia, Luyao Ma, Xiaoping Yin, Fei Yang, Bu-Lang Gao. Malignancy risk of gastrointestinal stromal tumors evaluated with noninvasive radiomics: A multi-center study. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.966743
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19 |
Peizhe Wang, Jingrui Yan, Hui Qiu, Jingying Huang, Zhe Yang, Qiang Shi, Chengxin Yan. A radiomics-clinical combined nomogram-based on non-enhanced CT for discriminating the risk stratification in GISTs. Journal of Cancer Research and Clinical Oncology 2023; 149(14): 12993 doi: 10.1007/s00432-023-05170-7
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20 |
Bing Kang, Xianshun Yuan, Hexiang Wang, Songnan Qin, Xuelin Song, Xinxin Yu, Shuai Zhang, Cong Sun, Qing Zhou, Ying Wei, Feng Shi, Shifeng Yang, Ximing Wang. Preoperative CT-Based Deep Learning Model for Predicting Risk Stratification in Patients With Gastrointestinal Stromal Tumors. Frontiers in Oncology 2021; 11 doi: 10.3389/fonc.2021.750875
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21 |
Maxime Barat, Anna Pellat, Benoit Terris, Anthony Dohan, Romain Coriat, Elliot K. Fishman, Steven P. Rowe, Linda Chu, Philippe Soyer. Cinematic Rendering of Gastrointestinal Stromal Tumours: A Review of Current Possibilities and Future Developments. Canadian Association of Radiologists Journal 2024; 75(2): 359 doi: 10.1177/08465371231211278
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22 |
Camilla Scapicchio, Michela Gabelloni, Andrea Barucci, Dania Cioni, Luca Saba, Emanuele Neri. A deep look into radiomics. La radiologia medica 2021; 126(10): 1296 doi: 10.1007/s11547-021-01389-x
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23 |
Federica Vernuccio, Roberto Cannella, Roberto Lagalla, Massimo Midiri. Computational Intelligence in Cancer Diagnosis. 2023; : 3 doi: 10.1016/B978-0-323-85240-1.00020-1
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24 |
Pak Kin Wong, In Neng Chan, Hao-Ming Yan, Shan Gao, Chi Hong Wong, Tao Yan, Liang Yao, Ying Hu, Zhong-Ren Wang, Hon Ho Yu. Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview. World Journal of Gastroenterology 2022; 28(45): 6363-6379 doi: 10.3748/wjg.v28.i45.6363
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