Comparison of three data mining models for prediction of advanced schistosomiasis prognosis in the Hubei province

<div><p>Background</p><p>In order to better assist medical professionals, this study aimed to develop and compare the performance of three models—a multivariate logistic regression (LR) model, an artificial neural network (ANN) model, and a decision tree (DT) model—to predict the prognosis of patients with advanced schistosomiasis residing in the Hubei province.</p><p>Methodology/Principal findings</p><p>Schistosomiasis surveillance data were collected from a previous study based on a Hubei population sample including 4136 advanced schistosomiasis cases. The predictive models use LR, ANN, and DT methods. From each of the three groups, 70% of the cases (2896 cases) were used as training data for the predictive models. The remaining 30% of the cases (1240 cases) were used as validation groups for performance comparisons between the three models. Prediction performance was evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Univariate analysis indicated that 16 risk factors were significantly associated with a patient’s outcome of prognosis. In the training group, the mean AUC was 0.8276 for LR, 0.9267 for ANN, and 0.8229 for DT. In the validation group, the mean AUC was 0.8349 for LR, 0.8318 for ANN, and 0.8148 for DT. The three models yielded similar results in terms of accuracy, sensitivity, and specificity.</p><p>Conclusions/Significance</p><p>Predictive models for advanced schistosomiasis prognosis, respectively using LR, ANN and DT models were proved to be effective approaches based on our dataset. The ANN model outperformed the LR and DT models in terms of AUC.</p></div

The establishment of the DT model for the prognosis of patients with advanced schistosomiasis (C4.5 algorithm).

<p>The establishment of the DT model for the prognosis of patients with advanced schistosomiasis (C4.5 algorithm).</p

ROC curves and AUC values for the advanced schistosomiasis prognosis models constructed with the validation groups using the ANN, DT, and LR models.

<p>The AUC value for the prognosis of patients with advanced schistosomiasis was 0.832 for the ANN model, 0.835 for the LR model, and 0.815 for the DT model. The AUC values of the ANN, DT, and LR models were approximate.</p

ROC curves and AUC values for the advanced schistosomiasis prognosis models constructed with the training groups using the ANN, DT, and LR models.

<p>The AUC value for the prognosis of patients with advanced schistosomiasis was 0.927 for the ANN model, 0.828 for the LR model, and 0.823 for the DT model. The AUC value of the ANN model was superior to those of the DT and LR models.</p