Application US20200143922

METHODS AND APPARATUS FOR PREDICTING DEPRESSION TREATMENT OUTCOMES
[+] Show Details

US20200143922

1. A system for providing a treatment recommendation for a patient having a depression disorder, the system comprising: (9) (1)

a server computer configured to: receive patient information including patient responses to each of a plurality of questions provided on a questionnaire;

process, with a trained statistical model, a set of values determined based, at least in part, on at least some of the received patient information to determine treatment recommendation information for the patient; and

transmit the treatment recommendation information to an electronic device.

2. The system of claim 1, wherein the set of values comprises a plurality of numerical values corresponding to features of the trained statistical model. (0)

3. The system of claim 1 wherein the trained statistical model comprises a plurality of decision trees and a weighting function that aggregates output from the plurality of decision trees. (0)

4. The system of claim 1, wherein the treatment recommendation information comprises a recommendation to treat the patient with one or more antidepressants selected from the group consisting of citalopram, escitalopram, and a combination of escitalopram and bupropion. (0)

5. The system of claim 1, wherein the server is further configured to perform symptom clustering on at least some of the received patient information. (2) (0)

9. The system of claim 1, wherein the server is further configured to instruct the electronic device to display a summary report of the treatment recommendation information on a user interface provided on the electronic device. (0)

10. The system of claim 1, wherein the server is further configured to convert one or more of the received patient information to a format acceptable as input to the trained statistical model. (0)

11. The system of claim 1, wherein an output of the trained statistical model is a plurality of values representing a percentage likelihood that a treatment will be effective for the patient, and wherein the server is further configured to determine the treatment recommendation information based on the plurality of values output from the trained statistical model. (0)

12. The system of claim 1, wherein the server is further configured to update the trained statistical model based, at least in part, on at least some of the received patient information and at least some of the treatment recommendation information. (0)

17. The method of claim 1, further comprising performing symptom clustering on at least some of the patient information. (1) (0)

13. A system for training a statistical model used to predict a treatment outcome for patients having depression, the system comprising: (2) (1)

a server computer configured to: determine a set of features to include in the statistical model;

train the statistical model using a first labeled dataset of values for the determined set of features, wherein the first labeled dataset includes clinical outcomes and patient information for each of a first plurality of patients; and

output the trained statistical model.

14. The system of claim 13, wherein the server is further configured to: (0) (1)

15. The system of claim 13, wherein determining the set of features to include in the statistical model identifying the features in the set of features by applying penalized logistic regression to the data in the first labeled dataset. (0)

16. A method of providing a treatment recommendation for a patient having a depression disorder, the method comprising: (1) (3)

processing using a trained statistical model executing on at least one computer processor, a set of values determined based, at least in part, on patient information including patient responses to each of a plurality of questions provided on a questionnaire;

determining treatment recommendation information based, at least in part, on output of the trained statistical model; and

transmitting the treatment recommendation information to an electronic device.

20. The method of claim 16, further comprising updating the trained statistical model based, at least in part, on at least some of the patient information and/or at least some of the determined treatment recommendation information. (0)

21. A system for classifying, based on their symptoms, patients having a depression disorder into one or more symptom cluster groups, the system comprising: (1) (1)

a server computer configured to: receive patient responses to each of a plurality of questions provided on a questionnaire by a plurality of patients;

apply a symptom clustering technique to the received patient responses to determine a plurality of symptom cluster groups; and

output a representation of the plurality of symptom cluster groups.

22. The system of claim 21, wherein the server computer is further configured to: (0) (3)

View Abstract and Specification Size

PDF with Images and Document Face >

Full Text Publication >

Application US20200143922

METHODS AND APPARATUS FOR PREDICTING DEPRESSION TREATMENT OUTCOMES

Patent Matrix® Search