An attention-based loss function and synthetic minority oversampling technique for alleviating class imbalance in predicting diabetes

An attention-based loss function and synthetic minority oversampling technique for alleviating class imbalance in predicting diabetes

Diabetes is a chronic disease due to higher blood sugar (or Glucose) levels in the blood. This study proposes a novel attention-based loss function and a lightweight artificial neural network (ANN) called Diabetic Lite (DB-Lite) for diabetes prediction in the Pima Indian Diabetes Dataset (PIDD). We...

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Bibliographic Details
Main Authors: Santanu Roy, Reshma Rachel Cherish, Gifty Roy
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Healthcare Analytics
Subjects:
Artificial neural network
Diabetes prediction
Class imbalance
Attention-based binary cross entropy
Synthetic minority oversampling technique (SMOTE)
Online Access:http://www.sciencedirect.com/science/article/pii/S2772442525000188
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