Systems and methods for clinical decision making for a patient receiving a neuromodulation therapy based on deep learning
US10729907B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 20, 2017 |
| Grant date | Aug 4, 2020 |
| Priority date | — |
| Expiry date | Aug 1, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H20/70
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
Information relevant to making clinical decisions for a patient is identified based on electrical activity records of the patient's brain and electrical activity records of other patients' brains. A deep learning algorithm is applied to an electrical activity record of the 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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.