| For: | Bredt LC, Peres LAB, Risso M, Barros LCAL. Risk factors and prediction of acute kidney injury after liver transplantation: Logistic regression and artificial neural network approaches . World J Hepatol 2022; 14(3): 570-582 [PMID: 35582300 DOI: 10.4254/wjh.v14.i3.570] |
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| URL: | https://www.wjgnet.com/1948-5182/full/v14/i3/570.htm |
| Number | Citing Articles |
| 1 |
Gidion Chongo, Jonathan Soldera. Use of machine learning models for the prognostication of liver transplantation: A systematic review. World Journal of Transplantation 2024; 14(1): 88891 doi: 10.5500/wjt.v14.i1.88891
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| 2 |
Jason Mann, Mathew Lyons, John O'Rourke, Simon Davies. Machine learning or traditional statistical methods for predictive modelling in perioperative medicine: A narrative review. Journal of Clinical Anesthesia 2025; 102 doi: 10.1016/j.jclinane.2025.111782
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| 3 |
Qian Gao, Lin Zhu, Ai-Jie Liu, Jie Gao, Xin-Yuan Kong, Jia-Ping Luan, Jin-Zhen Cai, He Dong. The association between potassium level during the anhepatic stage of orthotopic liver transplantation and postoperative acute kidney injury: an exploratory study. BMC Nephrology 2025; 26(1) doi: 10.1186/s12882-025-04337-3
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| 4 |
Allan R.M. França, Eduardo Rocha, Leonardo S.L. Bastos, Fernando A. Bozza, Pedro Kurtz, Elizabeth Maccariello, José Roberto Lapa e Silva, Jorge I.F. Salluh. Development and validation of a machine learning model to predict the use of renal replacement therapy in 14,374 patients with COVID-19. Journal of Critical Care 2024; 80 doi: 10.1016/j.jcrc.2023.154480
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| 5 |
Susana González-Suárez, Laura Llinares Espí, Manuel Grande Fernández, Juan José Ciudad Morales, Arantxa Vaque Cabeza, Clemente Antonio Durán Feliu, Paloma María Pereira Ricart, Lluís Castells Fuste, Gonzalo Sapisochin Cantis. Persistent Intraoperative Shock and Acute Kidney Injury After Liver Transplantation. Journal of Clinical Medicine 2026; 15(11) doi: 10.3390/jcm15114010
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| 6 |
Jingying Huang, Jiaojiao Chen, Jin Yang, Mengbo Han, Zihao Xue, Yina Wang, Miaomiao Xu, Haiou Qi, Yuting Wang. Prediction models for acute kidney injury following liver transplantation: A systematic review and critical appraisal. Intensive and Critical Care Nursing 2025; 86 doi: 10.1016/j.iccn.2024.103808
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| 7 |
Taiyo Kuroda, Barry D. Kuban, Takuma Miyamoto, Chihiro Miyagi, Anthony R. Polakowski, Christine R. Flick, Jamshid H. Karimov, Kiyotaka Fukamachi. Artificial Deep Neural Network for Sensorless Pump Flow and Hemodynamics Estimation During Continuous-Flow Mechanical Circulatory Support. ASAIO Journal 2023; 69(7) doi: 10.1097/MAT.0000000000001926
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| 8 |
Raja Al-Bahou, Julia Bruner, Helen Moore, Ali Zarrinpar. Quantitative methods for optimizing patient outcomes in liver transplantation. Liver Transplantation 2024; 30(3) doi: 10.1097/LVT.0000000000000325
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| 9 |
Feifei Lu, Yao Meng, Xiaoting Song, Xiaotong Li, Zhuang Liu, Chunru Gu, Xiaojie Zheng, Yi Jing, Wei Cai, Kanokwan Pinyopornpanish, Andrea Mancuso, Fernando Gomes Romeiro, Nahum Méndez-Sánchez, Xingshun Qi. Artificial Intelligence in Liver Diseases: Recent Advances. Advances in Therapy 2024; 41(3) doi: 10.1007/s12325-024-02781-5
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| 10 |
Nam-Jun Cho, Inyong Jeong, Se-Jin Ahn, Hyo-Wook Gil, Yeongmin Kim, Jin-Hyun Park, Sanghee Kang, Hwamin Lee. Machine Learning to Assist in Managing Acute Kidney Injury in General Wards: Multicenter Retrospective Study. Journal of Medical Internet Research 2025; 27 doi: 10.2196/66568
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| 11 |
Bing Bin, Yuxiao Chen, Shijian Li, Jihua Wu. Molecular Biomarkers and Risk Prediction Models for Acute Kidney Injury Following Liver Transplantation: A Review. Journal of Clinical and Experimental Hepatology 2026; 16(4) doi: 10.1016/j.jceh.2026.103550
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| 12 |
Parichat Tovikkai, Suvit Soontarinka, Manee Raksakietisak, Chutwichai Tovikkai, Orawan Pongraweewan, Arunotai Siriussawakul, Kittiphong Sujirattanawimol, Annop Piriyapatsom, Rattanaporn Tankul, Nattachai Hemtanon, Chularat Noinonthong, Chumsab Rattanaruangrit, Sutatta Boonyakarn, Aphichat Suphathamwit. The association of intraoperative hypotension during orthotopic liver transplantation and post-transplant outcomes. Asian Journal of Surgery 2025; 48(3) doi: 10.1016/j.asjsur.2024.11.213
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| 13 |
Alessia Nicosia, Nunzio Cancilla, José David Martín Guerrero, Ilenia Tinnirello, Andrea Cipollina. Artificial Intelligence in Nephrology: From Early Detection to Clinical Management of Kidney Diseases. Bioengineering 2025; 12(10) doi: 10.3390/bioengineering12101069
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| 14 |
Yordan Penev, Matthew M. Ruppert, Ahmet Bilgili, Youlei Li, Raiya Habib, Abdul-Vehab Dozic, Coulter Small, Esra Adiyeke, Tezcan Ozrazgat-Baslanti, Tyler J. Loftus, Chris Giordano, Azra Bihorac. Intraoperative hypotension and postoperative acute kidney injury: A systematic review. The American Journal of Surgery 2024; 232 doi: 10.1016/j.amjsurg.2024.02.001
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| 15 |
Xiang Yu, Yuwei Ji, Mengjie Huang, Zhe Feng. Machine learning for acute kidney injury: Changing the traditional disease prediction mode. Frontiers in Medicine 2023; 10 doi: 10.3389/fmed.2023.1050255
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| 16 |
Tinghua Zhang, Youyuan Hu, Chengdong Tang, Chunyan Yang. Current trends and future artificial intelligence applications in transfusion medicine: a bibliometric analysis. Expert Review of Hematology 2026; 19(1) doi: 10.1080/17474086.2025.2570336
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