Text Based Prediction of Psychological Cohorts

• US 20140222719A1
• Filed: 03/14/2013
• Published: 08/07/2014
• Est. Priority Date: 02/07/2013
• Status: Active Grant

• Current Assignee: Christian Poulin
• Original Assignee: Christian Poulin
• Inventors: Thompson, Paul, Vepstas, Linas, Poulin, Christian D.
• Granted Patent: US 9,817,949 B2
• Time in Patent Office: Days
• US Class Current: 706/11
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Computer implemented techniques for classifying mental states of individuals are described. The techniques determine sets of words that are associated with multiple groups having different mental status, and a classification model is used to classify one group against another group. Furthermore, by determining points of intersection of words between a first group and second group, words that are statistically predictive terms and that are unique to each group, to provide further predictive features for differentiating the multiple cohorts.

Claims

1. A computer implemented process comprises:

determining by one or more computers one or more data sets of words associated with multiple groups having different mental states define multiple cohorts;

executing by one or more computers a classification model of a first group to classify against a second group, with the first and second groups being of the multiple groups;

determining by one or more computers points of intersection of words between the first group and the second group; and

determining by one or more computers words that are unique to each group to provide isolated statistically predictive terms from the multiple groups for predictive features for corresponding ones of the multiple cohorts.

2. The method of claim 1 further comprising:

determining by the one or more computers a prediction of mental health status of the groups.

3. The method of claim 2 wherein the prediction is of suicidality risk.

4. The method of claim 2 wherein the prediction is suicidal ideation.

5. The method of claim 1 further comprising applying by the one or more computers a military veteran population dataset for suicidality prediction.

6. The method of claim 1 further comprising;

forming by the one or more computers ‘

contextualized word pairs’

to improve predictive accuracy.

7. The method of claim 1 wherein determining the model comprises

applying a machine learning system, including Bayesian algorithms to the dataset to predict mental state.

8. The method of claim 1 further comprises

applying a machine learning system, that includes genetic algorithms and genetic programming systems to predict mental state.

17. The product of claim 1 wherein determining the model comprises

apply a machine learning system, including Bayesian algorithms to the dataset to predict mental state.

9. A computer implemented process comprises:

determining by one or more computers one or more data sets of words associated with multiple groups having different mental states;

executing by one or more computers a classification model of a first group to classify against a second group;

determining by one or more computers points of intersection of words between the first group and the second group;

determining by one or more computers words that are unique to each group to provide isolated statistically predictive terms from multiple groups for predictive features for the group; and

applying a workflow process to reduce complexity in classification of groups or sub groups enabling a visualization of mental state cohorts for classification of risk.

10. The method of claim 9 further comprising:

determining by the one or more computers a prediction of mental health status of the groups.

11. A computer program product tangibly stored on a computer readable storage device, the computer program product for mental state classification comprises instructions for causing a processor to:

determine one or more data sets of words associated with multiple groups having different mental states define multiple cohorts;

execute a classification model of a first group to classify against a second group, with the first and second groups being of the multiple groups;

determine points of intersection of words between the first group and the second group; and

determine words that are unique to each group to provide isolated statistically predictive terms from the multiple groups for predictive features for corresponding ones of the multiple cohorts.

12. The product of claim 11 further comprising instructions to:

determining by the one or more computers a prediction of mental health status of the groups.

13. The product of claim 11 wherein the prediction is of suicidality risk.

14. The product of claim 11 wherein the prediction is suicidal ideation.

15. The product of claim 11 further comprising applying by the one or more computers a military veteran population dataset for suicidality prediction.

16. The product of claim 11 further comprising instructions to:

form contextualized word pairs to improve predictive accuracy.

18. The product of claim 11 further comprising instructions to

apply a machine learning system that includes genetic algorithms and genetic programming systems to predict mental state.

19. Apparatus, comprising:

a processor;

a memory coupled to the processor; and

a computer readable storage device storing a computer program product for mental state classification, the computer program product comprises instructions for causing the processor to;

determine one or more data sets of words associated with multiple groups having different mental states define multiple cohorts;

execute a classification model of a first group to classify against a second group, with the first and second groups being of the multiple groups;

determine points of intersection of words between the first group and the second group; and

determine words that are unique to each group to provide isolated statistically predictive terms from the multiple groups for predictive features for corresponding ones of the multiple cohorts.

20. The apparatus of claim 19 wherein the product further comprising instructions to

apply a machine learning system that includes genetic algorithms and genetic programming systems to predict mental state.