For: | Seyahi N, Ozcan SG. Artificial intelligence and kidney transplantation. World J Transplant 2021; 11(7): 277-289 [PMID: 34316452 DOI: 10.5500/wjt.v11.i7.277] |
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URL: | https://www.wjgnet.com/2220-3230/full/v11/i7/277.htm |
Number | Citing Articles |
1 |
Junseok Jeon, Jae Yong Yu, Yeejun Song, Weon Jung, Kyungho Lee, Jung Eun Lee, Wooseong Huh, Won Chul Cha, Hye Ryoun Jang. Prediction tool for renal adaptation after living kidney donation using interpretable machine learning. Frontiers in Medicine 2023; 10 doi: 10.3389/fmed.2023.1222973
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2 |
Rachel C. Forbes, Beatrice P. Concepcion. Left digit bias in donor organ acceptance: what can we do to make it right?. The American Journal of Surgery 2022; 224(4): 1103 doi: 10.1016/j.amjsurg.2022.05.039
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3 |
Kannan Sridharan, Shamik Shah. Developing supervised machine learning algorithms to evaluate the therapeutic effect and laboratory-related adverse events of cyclosporine and tacrolimus in renal transplants. International Journal of Clinical Pharmacy 2023; 45(3): 659 doi: 10.1007/s11096-023-01545-5
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4 |
Badi Rawashdeh. Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threats - Volume 2 [Working Title]. Artificial Intelligence 2024; 0 doi: 10.5772/intechopen.114356
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5 |
Zhe Yang, Minrui Zhang, Xianduo Li, Zhipeng Xu, Yi Chen, Xiaoyu Xu, Dongdong Chen, Lingquan Meng, Xiaoqing Si, Jianning Wang. Fluorescence spectroscopic profiling of urine samples for predicting kidney transplant rejection. Photodiagnosis and Photodynamic Therapy 2024; 45: 103984 doi: 10.1016/j.pdpdt.2024.103984
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6 |
Ekamol Tantisattamo, Antoney J. Ferrey, Uttam G. Reddy, Fatima T. Malik, Man Kit Michael Siu, Fawaz Al Ammary, Wei Ling Lau. A paradigm shift from office to home-based blood pressure measurement approaches in kidney transplant recipients. Current Opinion in Nephrology & Hypertension 2024; 33(1): 67 doi: 10.1097/MNH.0000000000000951
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7 |
Vidya Sankar Viswanathan, Paula Toro, Germán Corredor, Sanjay Mukhopadhyay, Anant Madabhushi. The state of the art for artificial intelligence in lung digital pathology. The Journal of Pathology 2022; 257(4): 413 doi: 10.1002/path.5966
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8 |
Tushar Bajaj, Jay L. Koyner. Artificial Intelligence in Acute Kidney Injury Prediction. Advances in Chronic Kidney Disease 2022; 29(5): 450 doi: 10.1053/j.ackd.2022.07.009
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9 |
Raquel M. Quinino, Fabiana Agena, Luis Gustavo Modelli de Andrade, Mariane Furtado, Alexandre D.P. Chiavegatto Filho, Elias David-Neto. A Machine Learning Prediction Model for Immediate Graft Function After Deceased Donor Kidney Transplantation. Transplantation 2023; 107(6): 1380 doi: 10.1097/TP.0000000000004510
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