Hearing outcome prediction estimator

A method comprising:

• receiving, by an application executed by a computing device, an input dataset of a user in a first user state, wherein the user is associated with a hearing aid device in the first user state;
• determining, by the application executed by the computing device, that the input dataset of the user includes a hearing performance result satisfying a hearing performance threshold;
• computing, in response to the determining that the input dataset of the user includes the hearing performance result satisfying the hearing performance threshold and by the application executed by the computing device using a trained machine learning model that was trained with one or more hearing aid datasets and one or more cochlear implant datasets, a predicted hearing performance of the user in a second user state based on the input dataset, wherein the user will be associated with a cochlear implant in the second user state;
• generating, by the application executed by the computing device, a visual representation of the predicted hearing performance of the user in the second user state;
• and
• presenting, by the application executed by the computing device, the visual representation of the predicted hearing performance on a display device.

A system comprising:

• a memory storing instructions;
• a processor communicatively coupled to the memory and configured to execute the instructions to:
• aggregate, by a hearing performance prediction system, a plurality of training examples, a training example in the plurality of training examples including a hearing aid dataset and a cochlear implant dataset associated with a user, the hearing aid dataset collected from a clinical facility of the user, a hearing aid device of the user, and an electronic device of the user, the cochlear implant dataset collected from the clinical facility of the user, a cochlear implant of the user, and an electronic device of the user;
• and
• train, by the hearing performance prediction system, a machine learning model using the plurality of training examples by:
• computing, using the machine learning model, a predicted hearing performance for the user based on the hearing aid dataset of the user in the training example;
• computing a feedback value based on the predicted hearing performance of the user and the cochlear implant dataset of the user in the training example;
• and
• adjusting one or more model parameters of the machine learning model based on the feedback value.