Classification of Diabetes Using Feature Selection and Hybrid Al-Biruni Earth Radius and Dipper Throated Optimization

Introduction: In public health, machine learning algorithms have been used to predict or diagnose chronic epidemiological disorders such as diabetes mellitus, which has reached epidemic proportions due to its widespread occurrence around the world. Diabetes is just one of several diseases for which...

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Vydané v:	Diagnostics (Basel) Ročník 13; číslo 12; s. 2038
Hlavní autori:	Alhussan, Amel Ali, Abdelhamid, Abdelaziz A., Towfek, S. K., Ibrahim, Abdelhameed, Eid, Marwa M., Khafaga, Doaa Sami, Saraya, Mohamed S.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 01.06.2023 MDPI
Predmet:	Accuracy Al-Biruni earth radius optimization Algorithms Chronic illnesses Classification Datasets Decision trees diabetes dipper throated optimization Disease Epidemiology Feature selection Forecasts and trends Gestational diabetes Hyperglycemia Insulin resistance Literature reviews Machine learning Mathematical optimization Medical research Medicine, Experimental Neural networks Optimization algorithms Optimization techniques Public health random forest Risk factors Support vector machines Type 2 diabetes random forest machine learning dipper throated optimization diabetes feature selection Al-Biruni earth radius optimization
ISSN:	2075-4418, 2075-4418
On-line prístup:	Získať plný text
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