  Sensorineural hearing loss can be treated using Cochlear implantation. After
this surgery using the electrode array impedance measurements, we can check the
stability of the impedance value and the dynamic range. Deterioration of speech
recognition scores could happen because of increased impedance values.
Medicines used to do these measures many times during a year after the surgery.
Predicting the electrode impedance could help in taking decisions to help the
patient get better hearing. In this research we used a dataset of 80 patients
of children who did cochlear implantation using MED-EL FLEX28 electrode array
of 12 channels. We predicted the electrode impedance on each channel after 1
month from the surgery date. We used different machine learning algorithms like
neural networks and decision trees. Our results indicates that the electrode
impedance can be predicted, and the best algorithm is different based on the
electrode channel. Also, the accuracy level varies between 66% and 100% based
on the electrode channel when accepting an error range between 0 and 3 KO.
Further research is required to predict the electrode impedance after three
months, six months and one year.
