Diabetes mellitus prediction and diagnosis from a data preprocessing and machine learning perspective
Computer Methods and Programs in Biomedicine(2022)
摘要
•Clinicians seek a reliable one-time diagnostic system for diabetes diagnosis without several blood sugar tests.•We framed working data pre-processing steps for feature selection and missing value imputation.•We developed a deep neural network model for accurately predicting diabetes mellitus and determining the disease severity during diagnosis.•A train and test prediction accuracies of 99.01% and 97.25% are achieved with the PIMA Indian dataset, while 99.57% and 97.33% accuracies are achieved with the LMCH dataset.•A performance difference that ranges from 8.68% to 21.99% is achieved in comparison to state-of-the-art.•This work can be reproduced with the publicly available source code.
更多查看译文
关键词
Diabetes mellitus,Machine learning,Deep neural networks,Data preprocessing,Polynomial regression,Spearman correlation
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要