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RESEARCH LETTER
Real-time prediction system for prevention of acute renal failure based on AI model
1
National Yunlin University of Science and Technology, Taiwan
Submission date: 2024-10-07
Final revision date: 2024-12-16
Acceptance date: 2024-12-28
Online publication date: 2024-12-31
TOPICS
REFERENCES (15)
2.
Ran L, Zhang YP, Guo L, Wang ZM, Zhang JM. Acute renal failure caused by Sjögren’s syndrome and rheumatoid arthritis overlap syndrome. Arch Med Sci 2024; 20: 1034-7.
3.
Kosiorek A, Tokarczyk W, Szymański O, Biegus J, Zymliński R. Timing of decongestion and its impact on acute heart failure prognosis. Arch Med Sci 2023; 19: 1551-7.
4.
Prabhu SN, Gooneratne CP, Hoang KA, Mukhopadhyay SC. IoT-associated impedimetric biosensing for point-of-care monitoring of kidney health. IEEE Sensors J 2021; 21: 14320-9.
5.
Wang HE, Muntner P, Chertow GM, Warnock DG. Acute kidney injury and mortality in hospitalized patients. Am J Nephrol 2012; 35: 349-55.
6.
Heidary Z, Ghaisari J, Moein S, Naderi M, Gheisari Y. Stochastic petri net modeling of hypoxia pathway predicts a novel incoherent feed-forward loop controlling SDF-1 expression in acute kidney injury. IEEE Trans Nanobioscience 2016; 15: 19-26.
7.
Shehata M, Khalifa F, Soliman A, et al. Computer-aided diagnostic system for early detection of acute renal transplant rejection using diffusion-weighted MRI. IEEE Trans Biomed Engineering 2019; 66: 539-52.
8.
Chen G, Ding C, Li Y, Hu X. Prediction of chronic kidney disease using adaptive hybridized deep convolutional neural network on the internet of medical things platform. IEEE Access 2020; 8: 100497-508.
9.
Guarda NS, Bollick YS, de Carvalho JAM, et al. High serum uric acid is associated with tubular damage and kidney inflammation in patients with type 2 diabetes. Dis Markers 2019; 2019, 6025804.
| eISSN: | 1896-9151 |
| ISSN: | 1734-1922 |
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