Resumen
Examining the relationship between the prognostic factors and the effectiveness of voice therapy is a crucial step in developing personalized treatment strategies for individuals with voice disorders. This study recommends using the multilayer perceptron model (MLP) to comprehensively analyze the prognostic factors, with various parameters, including personal habits and acoustic parameters, that can influence the effectiveness of before-and-after voice therapy in individuals with speech disorders. Various methods, including the assessment of personal characteristics, acoustic analysis, statistical analysis, binomial logistic regression analysis, and MLP, are implemented in this experiment. Accuracies of 87.5% and 85.71% are shown for the combination of optimal input parameters for female and male voices, respectively, through the MLP model. This fact validates the selection of input parameters when building our model. Good prognostic indicators for the clinical effectiveness of voice therapy in voice disorders are jitter (post-treatment) for females and MPT (pre-treatment) for males. The results are expected to provide a foundation for modeling research utilizing artificial intelligence in voice therapy for voice disorders. In terms of follow-up studies, it will be necessary to conduct research that utilizes big data to analyze the optimal parameters for predicting the clinical effectiveness of voice disorders.