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Prediction of diabetes using hybrid support vector machines with Artificial Bee Colony.

Published in:International Journal of Diabetes in Developing Countries Vol. 46; no. 2; pp. 469 - 485
Main Authors: Tared, Samira, Roubehie Fissa, Mohamed, Khaouane, Latifa, Hanini, Salah
Format: equations & formulas research tables/charts Journal Article
Published: Springer Nature Jun2026
Online Access:View this record in EBSCOhost
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      dt: Jun2026
      vid: 46
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      pub: Springer Nature
      place: New York, New York
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        atl: Prediction of diabetes using hybrid support vector machines with Artificial Bee Colony.
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          Tared, Samira
          Roubehie Fissa, Mohamed
          Khaouane, Latifa
          Hanini, Salah
        affil: https://ror.org/02e2yc259 Biomaterials and Transport Phenomena Laboratory (LBMPT), Faculty of Technology, Department of Process and Environmental Engineering, University of Yahia Fares, 26000, Medea, Algeria
      sug:
        subj:
          Diabetes Mellitus Diagnosis
          Support Vector Machine
          Artificial Intelligence
          Prediction Models Evaluation
          Diagnosis, Computer Assisted
          Sensitivity and Specificity Evaluation
          Early Diagnosis
          Detection Algorithms
          Human
          Validation Studies
          Neural Networks (Computer)
          Correlation Coefficient
          ROC Curve
          Descriptive Statistics
          Machine Learning Algorithms
          Precision
          India
          Male
          Female
          Data Analysis Software
          Comparative Studies
          Paired T-Tests
          Analysis of Variance
          Male
          Female
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
      ab:
    language: English
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