## 5 Conclusions  
Most previous studies have predicted the effects of voice therapy using objective measures such as voice analysis tests. However, in clinical practice, it is also important to consider subjective factors, such as patient satisfaction with treatment outcomes. Therefore, this study provides valuable insights into predicting voice therapy outcomes using the VHI. By analyzing various personal habits and clinical variables, we were able to identify key factors influencing the changes in VHI scores before and after voice therapy. Notably, gender, surgical history, frequency of voice use, and voice training status emerged as critical predictors of therapy outcomes; among these, gender was particularly significant, with female patients showing greater improvement in VHI scores compared to male patients. Surgical history and voice use status demonstrated high importance within the model, indicating that the physical causes of voice disorders and patterns of voice usage significantly impact therapeutic outcomes. For instance, patients with a history of surgery may experience more pronounced improvements in vocal condition post-therapy, while individuals who frequently use their voice may respond more sensitively to treatment due to the substantial impact on their quality of life. Clinically, these findings underscore the importance of voice training, emphasizing its positive role in sustaining and enhancing vocal function over time. Our analysis using the MLP model demonstrated the model's ability to effectively distinguish between positive and negative therapy outcomes, making it a valuable tool in clinical settings; however, the model's relatively low specificity indicates a limitation in accurately predicting cases for which therapy is ineffective, suggesting the need for further refinement to improve predictive accuracy.  
This research offers valuable guidance for clinicians and speech-language pathologists in predicting voice therapy outcomes and developing personalized treatment strategies that take individual patient characteristics into account. Future research should focus on validating these findings across larger and more diverse patient populations and exploring additional predictive variables to enhance the accuracy of the model; moreover, further studies are needed to refine the model's predictive power for various types of voice disorders. Such efforts will ultimately contribute to maximizing the effectiveness of voice therapy and improving the quality of life for patients with voice disorders.  
Data collection and analysis, J.H.P. and A.R.J.; conceptualization, J.-Y.L. and A.R.J.; software, J.-Y.L.; validation, J.-Y.L.; original draft preparation, J.-Y.L. and J.-N.L.; writing--review and editing, J.-Y.L. and A.R.J.; visualization, J.-N.L.; funding acquisition, J.-Y.L. All authors have read and agreed to the published version of the manuscript.  
This paper was supported by Eulji University in 2024 (2024-0114).  
This study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of Nowon Eulji Medical Center, Eulji University (IRB No. 2022-04-014).  
Not applicable.  
Data Availability StatementData were obtained from Nowon Eulji Medical Center and are available from Prof. [PERSON] with the permission of Nowon Eulji Medical Center.  
The authors declare no conflicts of interest.