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Date Published: 25/08/2023
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DOI: https://doi.org/10.51298/vmj.v529i1.6291
Issue
Vol. 529 No. 1 (2023)
Section
Các bài báo
How to Cite
Văn, H. T., Võ, M. T., Nguyễn, T. C. M., Lê, Q. T., Nguyễn, T. L., & Lê, T. M. D. (2023). INITIAL DETERMINATION OF THE PARAMETERS OF ARTIFICIAL NEURAL NETWORK IN ESTIMATED GLOMERULAR FILTRATION RATE. Vietnam Medical Journal, 529(1). https://doi.org/10.51298/vmj.v529i1.6291

INITIAL DETERMINATION OF THE PARAMETERS OF ARTIFICIAL NEURAL NETWORK IN ESTIMATED GLOMERULAR FILTRATION RATE

Hy Triết Văn1,2,, Minh Tuấn Võ1, Trương Công Minh Nguyễn1,2, Quốc Tuấn Lê1,2, Thị Lệ Nguyễn1,2, Thị Mai Dung Lê1
1 University of Medicine and Pharmacy at Ho Chi Minh City
2 City University of Medicine and Pharmacy Hospital. Ho Chi Minh campus 2

Main Article Content

Abstract

Objective: To find closely correlated parameters using an artificial neural network model that learns from eGFR formulas in biochemical analytes (glucose, albumin, protein, uric acid, urea, creatinine in blood and creatinine in urine) and biological parameters (age, sex, BMI, blood pressure, height, weight, waist circumference, buttock circumference) as the basis for building the next ANN models. Research method: Cross-sectional description of volunteers living in Ho Chi Minh City and Vung Tau, subjects with chronic kidney disease at kidney clinic, hospital of University of Medicine and Pharmacy of Ho Chi Minh City. Ho Chi Minh City basis 2. Survey of age, gender, height, weight, blood pressure, waist circumference, buttock circumference, BMI, glucose, urea, creatinine, protein, albumin uric acid in blood, and creatinine in water 24 hour urine. Results: There were 161 participants, including 115 healthy volunteers and 46 patients with chronic kidney disease. Determine 3 parameters of protein, serum creatinine, and weight that are closely correlated with the artificial neural network from established glomerular filtration rate estimation formulas. Conclusion: Using 3 analytes that are closely correlated with eGFR, namely protein, serum creatinine, and weight, data can be used to build an ANN model in estimating glomerular filtration rate

Article Details

Keywords

artificial neural network, estimated glomerular filtration rate, CKD-EPI, MDRD.

References

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