Abstract
We present in this paper some of the existing machine learning and sound processing techniques involved in the medical process and show how they can be applied in the context of a vocal disease detection task. The machine learning techniques are the usual, ranging from decision trees to neural networks, and when it comes to the sound processing approaches some scientists probably are familiar with them from the speech processing or music analysis areas. However, the techniques are adapted to the particularities of the medical field -- data collection, verification, etc. Through the concrete example of the vocal disease detection task we worked on, we made some interesting observations, both on the classification ability of the model and on the influence of the data.