SYSTEMS AND METHODS FOR CLINICAL DECISION MAKING FOR A PATIENT RECEIVING A NEUROMODULATION THERAPY BASED ON DEEP LEARNING

摘要

Information relevant to making clinical decisions for a subject patient is identified based on electrical activity records of the subject patient's brain and electrical activity records of other patients' brains. A deep learning algorithm is applied to an electrical activity record of the subject patient, i.e., an input record, and to a set of electrical activity records of other patients, i.e., a set of search records, to obtain an input feature vector of the patient and a set of search feature vectors, each including features extracted by the deep learning algorithm. A similarities algorithm is applied to the input feature vector and the set of search feature vectors to identify a subset of search records most like the input record. Clinical information associated with one or more search records in the identified subset of search records is extracted from a database and used to make decisions regarding the patient's neuromodulation therapies, or to make autonomous adjustments to therapies.