5 results for “Diabetes Risk Prediction”

Set a search alert

Research ArticleOpen accessPhrase in the titleImproving Diabetes Risk Prediction Using Ensemble Boosting and SMOTE-Based Class BalancingKittipol Wisaeng, Pankom Sriboonlue, Benchalak MuangmeesriAccurate diabetes prediction is vital for early intervention, optimized resource allocation, and minimizing long-term complications. This study presents a comparative evaluation of traditional and advanced machine learning models for diabetes classification using a structured clinical dataset. Seven baseline algorithms were assessed against five advanced ensemble methods: CatBoost, LightGBM, XGBoost, Voting Ensemble, and Stacking Ensemble. To improve algorithm learning, the Synthetic … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Feb 2026 · 1,976 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsPredicting Risk of Diabetes using a Model based on Multilayer Perceptron and Features ExtractionFrancesca Fallucchi, Alessandro CabroniDiabetes (diabetes mellitus) is a disease emerging when a person has a high blood sugar level for a prolonged period. In the healthcare context, one of the most important topic is the prevention of the disease. This study relates to diabetes prevention. In particular, it aims to produce random generated datasets according to a rule named Finnish Diabetes Risk Score … …Journal of Computer Science, Vol. 17, Issue 9 · 7 Sep 2021 · 6,580 accessesView PDF Cite

Research ArticleOpen accessIn the abstractIntelliHealth: A Machine Learning Driven Disease Detectionand Diet recommendation SystemAnkita Wadhwan, Priyanka Chawla, Sandeep Kaur, Usha MittalPeople all around the world are afflicted with various ailments. An accurate diagnosis can lower the risk of significant health problems developing, but an inaccurate diagnosis could have adverse implications. In this study, an ensemble-based strategy "IntelliHealth" has been presented to identify disorders of the thyroid, liver, and breast cancer using three machine learning (ML) approaches consisting of Support Vector … …Journal of Computer Science, Vol. 21, Issue 6 · 28 May 2025 · 5,226 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPredictive Modeling Applied to Structured Clinical Data Extracted from Electronic Health Records: An Architectural Hypothesis and A First ExperimentAlessandra Pieroni, Alessandro Cabroni, Francesca Fallucchi, Noemi ScarpatoPredictive analysis is one of current important issues in the healthcare context. A lot of patients’ input data can be obtained from their Electronic Health Records. In our research, we propose a general architecture named Health Prediction Architecture. Initially, we consider that data refer to strongly structured health datasets (no free text). Our objectives are related to exploring some problems … …Journal of Computer Science, Vol. 17, Issue 9 · 7 Sep 2021 · 6,571 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAn Analysis of Heart Disease for Diabetic Patients Using Recursive Feature Elimination with Random ForestBindushree Doddasiddavanahalli Channabasavaraju, Udayarani VinayakamurthyData Mining Techniques are used in many areas like banking, healthcare, education because of extracting relevant information from the database. Many algorithms in data mining are used to predict the disease to reduce the patient treatment cost as well as increase the diagnosis accuracy. In this research work, the risk level of diabetic heart disease patient can be predicted using … …Journal of Computer Science, Vol. 16, Issue 1 · 27 Jan 2020 · 7,931 accessesView PDF Cite