Using classified text and deep learning algorithms to identify medical risk and provide early warning
AssigneeIntraspexion Inc.
InventorsNelson E. Brestoff, Jonathan Brestoff Parker
Life of this patent
Estimating the term…
Abstract
Deep learning is used to identify specific, potential risks of missed diagnosis for a patient and reporting the risk to healthcare provider. The system involves mining and using existing electronic health records for specific medical diagnosis to train one or more deep learning algorithms, and then examining the internal electronic health record of the patient with the trained algorithm, to generate a scored output that will enable a healthcare provider to be alerted to potential risks of a missed diagnosis.
Claims11
A method of using classified text and deep learning algorithms to identify medical risk and provide early warning comprising:
- obtaining one or more training datasets for textual data corresponding to one or more risk classifications, wherein said risk classification comprises one or more specific medical diagnoses of interest;
- training one or more deep learning algorithms using said one or more training datasets;
- obtaining and indexing an internal electronic health record (EHR) of a patient;
- applying said one or more deep learning algorithms to said internal EHR to identify and report any one of said one or more specific medical diagnoses of interest;
- determining if said identified one of said one or more specific medical diagnoses of interest is a false positive or a true positive;
- and
- re-training said one or more deep learning algorithms if said identified one of said one or more specific medical diagnoses of interest is a false positive.
Dependencies are inferred from the claim text.