Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Roy, Santanu; Cherish, Reshma Rachel; Roy, Gifty Title A name given to the resource An attention-based loss function and synthetic minority oversampling technique for alleviating class imbalance in predicting diabetes Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Healthcare Analytics;Volume;7;Issue;;Article No.;100399; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.health.2025.100399" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.health.2025.100399</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105006933086?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105006933086?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Roy S., Pandit Deendayal Energy University (PDEU), Department of Computer Science and Engineering, Gandhinagar, India; Cherish R.R., Ramaiah Institute of Technology, Department of Computer Science and Engineering, Bangalore, India; Roy G., Christ (Deemed to be University), Department of Computer Science and Engineering, Bangalore, India Description An account of the resource 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 show that the Pima dataset has many challenges. It is a small and imbalanced dataset; moreover, many features are non-linearly correlated in this dataset. The novelties of this research work are as follows: (i) A novel loss function of attention-based binary cross entropy (ABCE) is proposed for the first time to alleviate the statistical imbalance present within the Pima dataset. This ABCE loss function is incorporated in the DB-Lite model, which is trained from scratch. (ii) A Swish activation function is deployed in the hidden layer of DB-Lite instead of Rectified Linear Unit (ReLU) to deal with the non-linear dependency of features with the final outcome. (iii) The synthetic minority oversampling technique (SMOTE) is used as a pre-processing technique to mitigate the class imbalance problem from the Pima dataset. (iv) An adaptive learning rate is utilized while training the model to speed up the convergence of the DB-Lite model. Our final proposed framework has achieved 99.7% accuracy, 99.4% precision, 99.8% recall, and 99.6% F1 score in testing, which is the best result on this Pima dataset. The Welch t-testing (as a statistical hypothesis testing) and 10-fold cross-validation are utilized to prove the validity of the proposed loss function. 2025 Subject The topic of the resource Artificial neural network; Attention-based binary cross entropy; Class imbalance; Diabetes prediction; Synthetic minority oversampling technique (SMOTE) Publisher An entity responsible for making the resource available Elsevier Inc. Relation A related resource ISSN: 27724425; Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online