Comparing Machine Learning Methods to Improve Fall Risk Detection in Elderly with Osteoporosis from Balance Data

<div>Graphic description of the mode of creation of the 45 models built with unbalanced data. <i>B</i> = Naïve Bayes classifier, <i>S</i> = support vector machine classifier, <i>K</i> = IBk classifier, <i>A</i> = AdaBoost classifier, and <i>R</i> = Random Forest classifier.</div>

Journal of Healthcare Engineering

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Figure 1

Figure 1: Comparing Machine Learning Methods to Improve Fall Risk Detection in Elderly with Osteoporosis from Balance Data 