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Inicio  /  Applied Sciences  /  Vol: 12 Par: 8 (2022)  /  Artículo
ARTÍCULO
TITULO

An Optimization-Based Diabetes Prediction Model Using CNN and Bi-Directional LSTM in Real-Time Environment

Parul Madan    
Vijay Singh    
Vaibhav Chaudhari    
Yasser Albagory    
Ankur Dumka    
Rajesh Singh    
Anita Gehlot    
Mamoon Rashid    
Sultan S. Alshamrani and Ahmed Saeed AlGhamdi    

Resumen

Diabetes is a common chronic disorder defined by excessive glucose levels in the blood. A good diagnosis of diabetes may make a person?s life better; otherwise, it can cause kidney failure, major heart damage, and damage to the blood vessels and nerves. As a result, diabetes classification and diagnosis are vital tasks. By using our proposed methodology, clinicians may obtain complete information about their patients using real-time monitoring. To gain new insights, they can combine historical information with current data, making it easier for them to perform more thorough and comprehensive treatments than before, and they will be able to provide proactive care, which will help to improve health outcomes and reduce hospital re-admissions.

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