Abstract: Systems and methods may be used to determine a fit for a hearing assistance device shell model. For example, a method may include receiving an image of anatomy of a patient including at least a portion of a canal aperture of an ear of the patient, generating a patient model of a portion of the anatomy of the patient, the patient model indicating at least one of a height or width of the canal aperture, and determining, using the patient model, a best fit model from a set of hearing assistance device shell models generated using a machine learning technique. The method may include outputting an identification of the best fit model.

Abstract: Systems and methods may be used to determine a fit for a hearing assistance device shell model. For example, a method may include receiving an image of anatomy of a patient including at least a portion of a canal aperture of an ear of the patient, generating a patient model of a portion of the anatomy of the patient, the patient model indicating at least one of a height or width of the canal aperture, and determining, using the patient model, a best fit model from a set of hearing assistance device shell models generated using a machine learning technique. The method may include outputting an identification of the best fit model.

Abstract: Systems and methods may be used to determine a fit for a hearing assistance device shell model. For example, a method may include receiving an image of anatomy of a patient including at least a portion of a canal aperture of an ear of the patient, generating a patient model of a portion of the anatomy of the patient, the patient model indicating at least one of a height or width of the canal aperture, and determining, using the patient model, a best fit model from a set of hearing assistance device shell models generated using a machine learning technique. The method may include outputting an identification of the best fit model.

Abstract: Systems and methods may be used to predict an applicable a hearing assistance device shell or model. For example, a method may include obtaining patient information, determining, using a machine learning trained model, a correlation between an input vector and each of a plurality of feature vectors corresponding to a plurality of hearing assistance device models, and ranking the plurality of hearing assistance device models based on respective correlations to the input vector. Information corresponding to a highest ranked hearing assistance device model may be output.

Abstract: Systems and methods may be used to determine a fit for a hearing assistance device shell model. For example, a method may include receiving an image of anatomy of a patient including at least a portion of a canal aperture of an ear of the patient, generating a patient model of a portion of the anatomy of the patient, the patient model indicating at least one of a height or width of the canal aperture, and determining, using the patient model, a best fit model from a set of hearing assistance device shell models generated using a machine learning technique. The method may include outputting an identification of the best fit model.