Enhanced early chronic kidney disease prediction using hybrid waterwheel plant algorithm for deep neural network optimization

Chronic Kidney Disease (CKD) is a progressive condition primarily caused by diabetes and hypertension, affecting millions worldwide. Early diagnosis remains a clinical challenge since traditional approaches, such as Glomerular Filtration Rate (GFR) estimation and kidney damage indicators, often fail...

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Vydáno v:	Scientific reports Ročník 15; číslo 1; s. 42584 - 23
Hlavní autoři:	Khafaga, Doaa Sami, Khodadadi, Nima, Khodadadi, Ehsaneh, Ali Alhussan, Amel, Eid, Marwa M, El-Kenawy, El-Sayed M
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England Nature Publishing Group 27.11.2025 Nature Portfolio
Témata:	Algorithms Biomarkers Chronic kidney disease prediction Deep Learning Deep neural networks Diabetes mellitus Early Diagnosis Early medical diagnosis Glomerular Filtration Rate Grey wolf optimization Humans Hybrid optimization algorithms Hypertension Kidney diseases Kidneys Mortality Neural networks Neural Networks, Computer Renal Insufficiency, Chronic - diagnosis Sensory integration Variance analysis Waterwheel plant algorithm Early medical diagnosis Grey wolf optimization Deep neural networks Hybrid optimization algorithms Chronic kidney disease prediction Waterwheel plant algorithm
ISSN:	2045-2322, 2045-2322
On-line přístup:	Získat plný text
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