A back propagation neural network approach to estimate the glomerular filtration rate in an older population

• Published in: BMC geriatrics Vol. 23; no. 1; pp. 322 - 10
• Main Authors: Jiang, Shimin, Li, Yetong, Jiao, Yuanyuan, Zhang, Danyang, Wang, Ying, Li, Wenge
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 24.05.2023; BioMed Central; BMC
• Subjects: Accuracy; Age groups; Aged; Analysis; Back propagation; Back propagation neural network; Bias; Care and treatment; Creatinine; Deep learning; Diabetes; Diagnosis; Elderly; Epidemiology; Estimation equation; Evaluation; Female; Geriatrics; Glomerular Filtration Rate; Humans; Independent variables; Kidney; Kidney diseases; Machine learning; Male; Neural networks; Neural Networks, Computer; Neurons; Older people; Pentetic Acid; Personal health; Renal Insufficiency, Chronic - diagnostic imaging; Serum creatinine; Software; Technetium; China; Back propagation neural network; Estimation equation; Elderly; Serum creatinine; Glomerular filtration rate

The use of creatinine-based glomerular filtration rate (GFR)-estimating equations to evaluate kidney function in elderly individuals does not appear to offer any performance advantages. We therefore aimed to develop an accurate GFR-estimating tool for this age group. Adults aged ≥ 65 years who under...