Systems and methods for audio recommendations for neural stimulations

Abstract

A system comprises a memory and one or more processors. The memory stores weights for a machine learning model. The weights are trained on a training data of a training set. The training data includes input audio signals, patient attributes, and measured brain response signals. The one or more processors are configured to receive an audio signal, determine a predicted brain response signal for the audio signal by applying the audio signal to the machine learning model, generate a flag for the audio signal based on whether the predicted brain response signal satisfies one or more stimulation criterion.

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