For: | Han IW, Cho K, Ryu Y, Shin SH, Heo JS, Choi DW, Chung MJ, Kwon OC, Cho BH. Risk prediction platform for pancreatic fistula after pancreatoduodenectomy using artificial intelligence. World J Gastroenterol 2020; 26(30): 4453-4464 [PMID: 32874057 DOI: 10.3748/wjg.v26.i30.4453] |
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URL: | https://www.wjgnet.com/1007-9327/full/v26/i30/4453.htm |
Number | Citing Articles |
1 |
Martina Nebbia, Giovanni Capretti, Gennaro Nappo, Alessandro Zerbi. Updates in the management of postoperative pancreatic fistula. International Journal of Surgery 2024; 110(10): 6135 doi: 10.1097/JS9.0000000000001395
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2 |
Chie Takasu, Masaaki Nishi, Kozo Yoshikawa, Takuya Tokunaga, Hideya Kashihara, Yuma Wada, Toshiaki Yoshimoto, Mitsuo Shimada. Preoperative evaluation to determine the difficulty of No. 6 lymphadenectomy in laparoscopic gastrectomy. BMC Surgery 2024; 24(1) doi: 10.1186/s12893-024-02349-8
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Sohan Lal Solanki, Saneya Pandrowala, Abhirup Nayak, Manish Bhandare, Reshma P Ambulkar, Shailesh V Shrikhande. Artificial intelligence in perioperative management of major gastrointestinal surgeries. World Journal of Gastroenterology 2021; 27(21): 2758-2770 doi: 10.3748/wjg.v27.i21.2758
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4 |
Guohua Zhao, Xi Chen, Mengying Zhu, Yang Liu, Yue Wang. Exploring the application and future outlook of Artificial intelligence in pancreatic cancer. Frontiers in Oncology 2024; 14 doi: 10.3389/fonc.2024.1345810
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5 |
Imtiakum Jamir, Niteen Kumar, Gaurav Sood, Abhideep Chaudhary. Complications of Cancer Therapy: Best Practices in Prevention and Management. 2024; : 407 doi: 10.1007/978-981-99-0984-1_35
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6 |
Kevin A. Chen, Matthew E. Berginski, Chirag S. Desai, Jose G. Guillem, Jonathan Stem, Shawn M. Gomez, Muneera R. Kapadia. Differential Performance of Machine Learning Models in Prediction of Procedure-Specific Outcomes. Journal of Gastrointestinal Surgery 2022; 26(8): 1732 doi: 10.1007/s11605-022-05332-x
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7 |
Ziying Lin, Bingjun Tang, Jinxiu Cai, Xiangpeng Wang, Changxin Li, Xiaodong Tian, Yinmo Yang, Xiaoying Wang. Preoperative prediction of clinically relevant postoperative pancreatic fistula after pancreaticoduodenectomy. European Journal of Radiology 2021; 139: 109693 doi: 10.1016/j.ejrad.2021.109693
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8 |
Mona Saleh, Mohammad AlHamaydeh, Mohamed Zakaria. Shear capacity prediction for reinforced concrete deep beams with web openings using artificial intelligence methods. Engineering Structures 2023; 280: 115675 doi: 10.1016/j.engstruct.2023.115675
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9 |
Olexii I. Dronov, Inna O. Kovalska, Andrii I. Horlach, Ivanna A. Shchyhel. PREDICTION OF EXTERNAL PANCREATIC FISTULA DEVELOPMENT IN PATIENTS WITH ACUTE INFECTED NECROTISING PANCREATITIS. Wiadomości Lekarskie 2023; 76(11): 2365 doi: 10.36740/WLek202311104
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10 |
So-Jeong Yoon, So-Kyung Yoon, Ji-Hye Jung, In-Woong Han, Dong-Wook Choi, Jin-Seok Heo, Sang-Hyun Shin. Realistic Advantages of Early Surgical Drain Removal after Pancreatoduodenectomy: A Single-Institution Retrospective Study. Journal of Clinical Medicine 2021; 10(12): 2716 doi: 10.3390/jcm10122716
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11 |
Christoph Kuemmerli, Fabian Rössler, Caroline Berchtold, Michael C. Frey, Alexander Studier-Fischer, Amila Cizmic, Jan Philipp Jonas, Thilo Hackert, Felix Nickel, Philip C. Müller. Artificial intelligence in pancreatic surgery: current applications. Journal of Pancreatology 2023; 6(2): 74 doi: 10.1097/JP9.0000000000000129
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12 |
Zahraa M. Alhulaili, Ralph J. Linnemann, Larisa Dascau, Rick G. Pleijhuis, Joost M. Klaase. A Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis analysis to evaluate the quality of reporting of postoperative pancreatic fistula prediction models after pancreatoduodenectomy: A systematic review. Surgery 2023; 174(3): 684 doi: 10.1016/j.surg.2023.04.058
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13 |
Hager Saleh, Nora El-Rashidy, Eman Mohamed, Ahmad M Sultan, Ayman El Nakeeb, Shaker El-Sappagh. Machine learning model for predicting pancreatic fistula after pancreatoduodenectomy. 2023 Intelligent Methods, Systems, and Applications (IMSA) 2023; : 217 doi: 10.1109/IMSA58542.2023.10217619
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14 |
T. A. Samgina. Predicting the course and outcome of acute alcoholic-alimentary pancreatitis, taking into account the genetic status of the patient according to the polymorphic loci rs11546155 and rs6119534 of the GGT7 gene. Experimental and Clinical Gastroenterology 2023; (8): 35 doi: 10.31146/1682-8658-ecg-204-8-35-40
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15 |
Giulia Pacella, Maria Chiara Brunese, Eleonora D’Imperio, Marco Rotondo, Andrea Scacchi, Mattia Carbone, Germano Guerra. Pancreatic Ductal Adenocarcinoma: Update of CT-Based Radiomics Applications in the Pre-Surgical Prediction of the Risk of Post-Operative Fistula, Resectability Status and Prognosis. Journal of Clinical Medicine 2023; 12(23): 7380 doi: 10.3390/jcm12237380
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16 |
Woohyung Lee, Hyo Jung Park, Hack-Jin Lee, Ki Byung Song, Dae Wook Hwang, Jae Hoon Lee, Kyongmook Lim, Yousun Ko, Hyoung Jung Kim, Kyung Won Kim, Song Cheol Kim. Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula. Scientific Reports 2024; 14(1) doi: 10.1038/s41598-024-51777-2
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17 |
Hua Yin, Feixiong Zhang, Xiaoli Yang, Xiangkun Meng, Yu Miao, Muhammad Saad Noor Hussain, Li Yang, Zhaoshen Li. Research trends of artificial intelligence in pancreatic cancer: a bibliometric analysis. Frontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.973999
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18 |
Ankit Shukla, Rajesh Chaudhary, Nishant Nayyar. Role of artificial intelligence in gastrointestinal surgery. Artificial Intelligence in Cancer 2024; 5(2): 97317 doi: 10.35713/aic.v5.i2.97317
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19 |
Akseli Bonsdorff, Ville Sallinen. Prediction of postoperative pancreatic fistula and pancreatitis after pancreatoduodenectomy or distal pancreatectomy: A review. Scandinavian Journal of Surgery 2023; 112(2): 126 doi: 10.1177/14574969231167781
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20 |
Nicolò Cardobi, Riccardo De Robertis, Mirko D’Onofrio. Imaging and Pathology of Pancreatic Neoplasms. 2022; : 481 doi: 10.1007/978-3-031-09831-4_13
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21 |
Jian Su, Mengyao Li, Xinglin Wan, Hao Yu, Yanan Wan, Dong Hang, Yan Lu, Ran Tao, Ming Wu, Jinyi Zhou, Xikang Fan. Associations of diabetes, prediabetes and diabetes duration with the risk of chronic obstructive pulmonary disease: A prospective UK Biobank study. Diabetes, Obesity and Metabolism 2023; 25(9): 2575 doi: 10.1111/dom.15142
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22 |
Giovanni Capretti, Cristiana Bonifacio, Crescenzo De Palma, Martina Nebbia, Caterina Giannitto, Pierandrea Cancian, Maria Elena Laino, Luca Balzarini, Nickolas Papanikolaou, Victor Savevski, Alessandro Zerbi. A machine learning risk model based on preoperative computed tomography scan to predict postoperative outcomes after pancreatoduodenectomy. Updates in Surgery 2022; 74(1): 235 doi: 10.1007/s13304-021-01174-5
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23 |
Feng Yang, John A Windsor, De-Liang Fu. Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives. World Journal of Gastroenterology 2024; 30(10): 1329-1345 doi: 10.3748/wjg.v30.i10.1329
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24 |
Valentina Bianchi, Mauro Giambusso, Alessandra De Iacob, Maria Michela Chiarello, Giuseppe Brisinda. Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review. Updates in Surgery 2024; 76(3): 783 doi: 10.1007/s13304-024-01801-x
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Po‐Ting Chen, Dawei Chang, Tinghui Wu, Ming‐Shiang Wu, Weichung Wang, Wei‐Chih Liao. Applications of artificial intelligence in pancreatic and biliary diseases. Journal of Gastroenterology and Hepatology 2021; 36(2): 286 doi: 10.1111/jgh.15380
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So Jeong Yoon, Wooil Kwon, Ok Joo Lee, Ji Hye Jung, Yong Chan Shin, Chang-Sup Lim, Hongbeom Kim, Jin-Young Jang, Sang Hyun Shin, Jin Seok Heo, In Woong Han. External validation of risk prediction platforms for pancreatic fistula after pancreatoduodenectomy using nomograms and artificial intelligence. Annals of Surgical Treatment and Research 2022; 102(3): 147 doi: 10.4174/astr.2022.102.3.147
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D. Schlanger, F. Graur, C. Popa, E. Moiș, N. Al Hajjar. The role of artificial intelligence in pancreatic surgery: a systematic review. Updates in Surgery 2022; 74(2): 417 doi: 10.1007/s13304-022-01255-z
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Wessel T. Stam, Lotte K. Goedknegt, Erik W. Ingwersen, Linda J. Schoonmade, Emma R.J. Bruns, Freek Daams. The prediction of surgical complications using artificial intelligence in patients undergoing major abdominal surgery: A systematic review. Surgery 2022; 171(4): 1014 doi: 10.1016/j.surg.2021.10.002
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Zhi-Da Long, Chao Lu, Xi-Gang Xia, Bo Chen, Zhi-Xiang Xing, Lei Bie, Peng Zhou, Zhong-Lin Ma, Rui Wang. Personal predictive model based on systemic inflammation markers for estimation of postoperative pancreatic fistula following pancreaticoduodenectomy. World Journal of Gastrointestinal Surgery 2022; 14(9): 963-975 doi: 10.4240/wjgs.v14.i9.963
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Wessel T. Stam, Erik W. Ingwersen, Mahsoem Ali, Jorik T. Spijkerman, Geert Kazemier, Emma R. J. Bruns, Freek Daams. Machine learning models in clinical practice for the prediction of postoperative complications after major abdominal surgery. Surgery Today 2023; 53(10): 1209 doi: 10.1007/s00595-023-02662-4
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Jisheng Zheng, Xiaoqin Lv, Lihui Jiang, Haiwei Liu, Xiaomin Zhao. Development of a Pancreatic Fistula Prediction Model After Pancreaticoduodenectomy Based on a Decision Tree and Random Forest Algorithm. The American Surgeon 2023; : 000313482311586 doi: 10.1177/00031348231158692
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