Predicting the Emergence of Hyperglycaemia through the Application of Machine Learning Methodologies

Le résumé fourni par la source

Hyperglycaemia is a lifelong digestive condition that causes excessive blood sugar levels. Early detection along with treatment can avoid or prolong the problems in their beginning. Earlier studies have used machine learning to predict pathology. This study suggests that an artificially intelligent neural network could be a beneficial tool for managing and preventing diabetes. Hyperglycaemia can lead to both acute and chronic consequences, including fatalities. Chronic problems can lead to various impairments and organ deterioration. Failure to provide comprehensive remedies and preventions for diabetes patients can result in increased medical costs and a reduction in society’s overall quality of life. Eight subject parameters were examined in this study: age, body mass index, plasma glucose level, insulin level, diastolic blood pressure, sebum thickness, pregnancies’ number, and diabetes pedigree function. This study used to build neural network models and assess their accuracy in predicting diabetes. Results showed that some models performed better than others.

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