Updating a clinical trial participation status based on a measure of trust dynamics

Patent metadata

Field	Value
Publication number	US-11688491-B2
Application number	US-202017134686-A
Country	US
Kind code	B2
Filing date	Dec 28, 2020
Priority date	May 22, 2018
Publication date	Jun 27, 2023
Grant date	Jun 27, 2023

Abstract

Techniques regarding autonomously updating a participation status of an entity with regards to a clinical trial are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise status component that can update a participation status of an entity regarding a clinical trial based on a trust disposition value. The trust disposition value can be determined using machine learning technology and can be indicative of an expected enrichment contribution associated with the participation status.

First claim

What is claimed is:

1. A system, comprising:
a memory that stores computer executable components;
a processor, operably coupled to the memory, and that executes the computer executable components stored in the memory, wherein the computer executable components comprise:
a data analysis component that trains a neural network to determine trust disposition values associated with human entities based on interactions with the human entities, wherein the interactions comprises chatbot conversations with the human entities directed to at least one commitment involving the human entities with respect to at least one medical related experience of the human entities, and wherein the trust disposition value represents a likeliness of the human entity to trust at least one part of at least one clinical trial;
an evaluation component that determines, using the neural network, a trust disposition value associated with a human entity by analyzing a dataset associated with interactions with the human entity, wherein the interaction comprise at least one chatbot conversation with the human entity; and
a status component that updates a participation status of the human entity regarding a clinical trial based on the trust disposition value.

2. The system of claim 1 , wherein the data analysis component that generates the dataset that comprises a plurality of features extracted from the interactions with the human entity.

3. The system of claim 2 , wherein the plurality of features comprise features selected from a group consisting of a debtor, a creditor, an antecedent, and a consequent.

4. The system of claim 2 , wherein at least one of the interactions with the human entity relates to a commitment involving the human entity with respect to at least one medical related experience of the human entity, and wherein the plurality of features delineates whether the commitment was fulfilled.

5. The system of claim 1 , wherein the at least one medical experience comprises at least one of a medical treatment or a prescribed medicine.

6. The system of claim 1 , wherein the status component updates the participation status further based on an expected enrichment contribution of the human entity that is selected from a group consisting of a decrease in heterogeneity amongst a population studied by the clinical trial, a prognostic enrichment of the clinical trial, and a predictive enrichment of the clinical trial.

7. The system of claim 1 , wherein the clinical trial studies an effect of a chemical compound on a group of human entities.

8. A computer-implemented method, comprising:
training, by a system operatively coupled to a processor, an artificial intelligence model to determine trust disposition values associated with human entities based on interactions with the human entities, wherein the interactions comprises chatbot conversations with the human entities directed to at least one commitment involving the human entities with respect to at least one medical related experience of the human entities, and wherein the trust disposition value represents a likeliness of the human entity to trust at least one part of at least one clinical trial;
determining, by the system, using the artificial intelligence model, a trust disposition value associated with a human entity by analyzing a dataset associated with interactions with the human entity, wherein the interaction comprise at least one chatbot conversation with the human entity; and
updating, by the system, a participation status of the human entity regarding a clinical trial based on the trust disposition value.

9. The computer-implemented method of claim 8 , further comprising:
generating, by the system, the dataset that comprises a plurality of features extracted from the interactions with the human entity.

10. The computer-implemented method of claim 9 , wherein the plurality of features comprise features selected from a group consisting of a debtor, a creditor, an antecedent, and a consequent.

11. The computer-implemented method of claim 9 , wherein at least one of the interactions with the human entity relates to a commitment involving the human entity with respect to at least one medical related experience of the human entity, and wherein the plurality of features delineates whether the commitment was fulfilled.

12. The computer-implemented method of claim 8 , wherein the at least one medical experience comprises at least one of a medical treatment or a prescribed medicine.

13. The computer-implemented method of claim 8 , further comprising:
updating, by the system, the participation status further based on an expected enrichment contribution of the human entity that is selected from a group consisting of a decrease in heterogeneity amongst a population studied by the clinical trial, a prognostic enrichment of the clinical trial, and a predictive enrichment of the clinical trial.

14. The computer-implemented method of claim 8 , wherein the clinical trial studies an effect of a chemical compound on a group of human entities.

15. A computer program product for enriching a clinical trial population, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
training a machine learning model to determine trust disposition values associated with human entities based on interactions with the human entities, wherein the interactions comprises chatbot conversations with the human entities directed to at least one commitment involving the human entities with respect to at least one medical related experience of the human entities, and wherein the trust disposition value represents a likeliness of the human entity to trust at least one part of at least one clinical trial;
determine, using the machine learning model, a trust disposition value associated with a human entity by analyzing a dataset associated with interactions with the human entity, wherein the interaction comprise at least one chatbot conversation with the human entity; and
update a participation status of the human entity regarding a clinical trial based on the trust disposition value.

16. The computer program product of claim 15 , wherein the program instructions further cause the processor to:
generate the dataset that comprises a plurality of features extracted from the interactions with the human entity.

17. The computer program product of claim 16 , wherein the plurality of features comprise features selected from a group consisting of a debtor, a creditor, an antecedent, and a consequent.

18. The computer program product of claim 16 , wherein at least one of the interactions with the human entity relates to a commitment involving the human entity with respect to at least one medical related experience of the human entity, and wherein the plurality of features delineates whether the commitment was fulfilled.

19. The computer program product of claim 15 , wherein the at least one medical experience comprises at least one of a medical treatment or a prescribed medicine.

20. The computer program product of claim 15 , wherein the program instructions further cause the processor to:
update the participation status further based on an expected enrichment contribution of the human entity that is selected from a group consisting of a decrease in heterogeneity amongst a population studied by the clinical trial, a prognostic enrichment of the clinical trial, and a predictive enrichment of t

Assignees

• IBM

Inventors

• Kozloski James R
• Berger Sara
• Kalia Anup
• Rogers Jeffrey L

Classifications

• G06N20/00

  Machine learning · CPC title

• G16H10/20 Primary

  for electronic clinical trials or questionnaires · CPC title

• G06N3/006

  based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO] · CPC title