Evaluating the Effects of Noise on Machine Learning Models in Voice Disorder Diagnosis

Assessing Noise Impact

In the field of voice disorder evaluation, noise can significantly alter the effectiveness of machine learning models. By identifying the types of noise that most affect these models, researchers can improve the accuracy of diagnostic tools.

Factors Influencing Performance

• Types of noise
• Data accuracy
• Model reliability

Conclusion

Addressing the impact of noise is essential for enhancing the performance of machine learning in voice disorder diagnosis, ultimately benefiting patient health outcomes.