Systems and methods for clinical decision making for a patient receiving a neuromodulation therapy based on deep learning

A processor for selecting stimulation parameter settings for a neurostimulation system associated with a patient, the processor comprising:

• a similarities module configured to:
• obtain at least one input feature vector comprising a plurality of different features extracted by a deep learning algorithm from at least one input record of the patient;
• obtain a set of search feature vectors, each comprising a plurality of different features extracted by a deep learning algorithm from a search record included in a set of search records of other patients;
• apply a similarities algorithm to the at least one input feature vector and the set of search feature vectors to identify a subset of search records having a measure of similarity with the at least one input record, which measure meets a predetermined criterion;
• and
• an extraction module configured to extract from a database, clinical information associated with one or more of the search records of other patients in the identified subset of search records of other patients, the clinical information comprising the stimulation parameter settings of other patients for the neurostimulation system, wherein the stimulation parameter settings of other patients define a stimulation therapy deliverable by the neurostimulation system and comprise at least one of amplitude, pulse width, burst duration, and frequency.