Blood glucose prediction model for type 1 diabetes based on artificial neural network with time-domain features
Abstract
Predicting future blood glucose (BG) levels for diabetic patients will help them avoid potentially critical health issues.
Abstract
Predicting future blood glucose (BG) levels for diabetic patients will help them avoid potentially critical health issues.
Abstract
Extracting information from individual risk factors provides an effective way to identify diabetes risk and associated complications, such as retinopathy, at an early stage.

Abstract
Detecting self-care problems is one of important and challenging issues for occupational therapists, since it requires a complex and time-consuming process.

Abstract
Heart disease, one of the major causes of mortality worldwide, can be mitigated by early heart disease diagnosis.
Abstract
Predicting future blood glucose (BG) level for diabetic patients will help them to avoid critical conditions in the future.
Abstract
Early diseases prediction plays an important role for improving healthcare quality and can help individuals avoid dangerous health situations before it is too late.