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September 10, 2025Journal of interdisciplinary perspectives

Predictive Modeling of Diabetes Classification using Binomial Logistic Regression on Biomedical Indicators

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Authors

JCJojie CampuganMAMelani Aguaras

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Overview

Predictive model classifies diabetes using binomial logistic regression and biomedical indicators, suggesting improved screening in underserved communities.

Key Points

  • The predictive model successfully classifies individuals as diabetic or non-diabetic based on biomedical indicators.
  • Binomial logistic regression identified Body Mass Index as the most significant predictor of diabetes risk.
  • K-means clustering categorized participants into high and low diabetes risk groups based on biomarker profiles.
  • Integration of predictive analytics into healthcare could empower communities to adopt necessary preventive measures.

Cite This Study

Campugan et al. (2025) studied this question.

synapsesocial.com/papers/68c1bd4254b1d3bfb60eea32https://doi.org/10.69569/jip.2025.465
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Also Consider

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  1. 1Comparative Analysis of Machine Learning Models for Diabetes Risk Prediction Using Clinical Health Indicators2026
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  4. 4Evaluating Diabetes Risk: Bayesian Hierarchical Models and Machine Learning Integration2024
  5. 5Diabetes Risk Prediction Based on Clinical and Lifestyle Data2026