Diabetes Detection Models in Mexican Patients by Combining Machine Learning Algorithms and Feature Selection Techniques for Clinical and Paraclinical Attributes: A Comparative Evaluation

<table class="table-group" id="tab7"><tr><td><table class="table"><tr><td class="thead-hr" colspan="1"><hr/></td></tr><tr class="thead"><td class="align_left">Features selected</td></tr><tr><td class="thead-hr" colspan="1"><hr/></td></tr><tr><td class="align_left">EDUCATION</td></tr><tr><td class="align_left">GLUCOSE</td></tr><tr><td class="align_left">Age</td></tr><tr><td class="align_left">HIP.perimetro.abdominal</td></tr><tr><td class="align_left">MMOLGLUC</td></tr><tr class="table-tr"><td colspan="1"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Features selected using the Galgo genetic algorithm.</div>

Journal of Diabetes Research

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Table 7

Table 7: Diabetes Detection Models in Mexican Patients by Combining Machine Learning Algorithms and Feature Selection Techniques for Clinical and Paraclinical Attributes: A Comparative Evaluation 

Table 7 | Diabetes Detection Models in Mexican Patients by Combining Machine Learning Algorithms and Feature Selection Techniques for Clinical and Paraclinical Attributes: A Comparative Evaluation 