Early Stage Diabetes Prediction via Extreme Learning Machine

被引:3
|
作者
Elsayed, Nelly [1 ]
ElSayed, Zag [1 ]
Ozer, Murat [1 ]
机构
[1] Univ Cincinnati, Sch Informat Technol, Cincinnati, OH 45221 USA
来源
SOUTHEASTCON 2022 | 2022年
关键词
Diabetes; ELM; extreme learning machine; prediction;
D O I
10.1109/SoutheastCon48659.2022.9764032
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Diabetes is one of the chronic diseases that has been discovered for decades. However, several cases are diagnosed in their late stages. Every one in eleven of the world's adult population has diabetes. Forty-six percent of people with diabetes have not been diagnosed. Diabetes can develop several other severe diseases that can lead to patient death. Developing and rural areas suffer the most due to the limited medical providers and financial situations. This paper proposed a novel approach based on an extreme learning machine for diabetes prediction based on a data questionnaire that can early alert the users to seek medical assistance and prevent late diagnoses and severe illness development.
引用
收藏
页码:374 / 379
页数:6
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