Systems and methods for using machine learning to improve processes for achieving readiness

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for using machine learning to improve processes for achieving readiness. In some implementations, a database is accessed to obtain status data that indicates activities or attributes of a subject. One or more readiness scores indicating a level of capability of the subject to satisfy one or more readiness criteria are generated. Data is accessed indicating multiple candidate actions for improving capability of the subject to satisfy one or more readiness criteria. A subset of the candidate actions for the subject are selected based on the one or more readiness scores generated using the one or more models. Output is provided to cause one or more of the actions in the selected subset to be performed or cause an indication one or more of the actions in the selected subset to be presented on a user interface.

What is claimed is: 
     
         1 - 20 . (canceled) 
     
     
         21 . A method performed by one or more computers, the method comprising:
 monitoring, by the one or more computers, data indicating activities or attributes of each participant in a group of multiple participants in a health research study, wherein the monitoring for each participant includes acquiring health data provided by an electronic device of the participant to the one or more computers over a communication network;   evaluating, by the one or more computers, the monitoring data for each of the participants in the group to predict readiness of the participants to receive one or more therapeutic interventions, including:
 deriving, for each participant, a set of scores from the monitoring data for the participant, the set of scores including values indicative of attributes or activities of the participant from monitoring data for the participant; and 
 generating, for each participant, output indicative of whether the participant is ready to receive the one or more therapeutic interventions, the output being generated by providing the set of scores to one or more models that have been configured to predict readiness of participants to receive a therapeutic intervention; 
   based on output of the one or more models, determining, by the one or more computers, whether the participants are respectively ready to receive the one or more therapeutic interventions; and   altering, by the one or more computers, interactions of the electronic devices with the participants to selectively provide therapeutic interventions in the health research study based on the determinations for the participants.   
     
     
         22 . The method of  claim 21 , wherein the group of participants is a cohort of participants for a clinical trial. 
     
     
         23 . The method of  claim 21 , wherein altering interactions with the participants comprises adjusting a frequency or type of health monitoring performed for one or more of the participants in the group. 
     
     
         24 . The method of  claim 21 , wherein the set of scores including values indicative of attributes or activities of the participant comprises value indicating physiological measurements for the participant or measures of behavior of the participant. 
     
     
         25 . The method of  claim 21 , wherein the one or more models are machine learning models that have been trained based on examples indicating attributes or activities of other participants and outcomes of providing the one or more therapeutic interventions to the other participants. 
     
     
         26 . The method of  claim 21 , further comprising generating a group readiness measure that provides an aggregate measure of readiness of the group of participants subjects for the one or more therapeutic interventions;
 wherein the interactions of the health research study that are provided through the electronic devices to the participants are based at least in part on the aggregate measure of readiness.   
     
     
         27 . The method of  claim 21 , further comprising using at least one model to predict likelihoods of completion of the health research study by the respective participants. 
     
     
         28 . A system comprising:
 one or more computers; and   one or more computer-readable media storing instructions that, when executed, cause the one or more computers to perform operations comprising:
 monitoring, by the one or more computers, data indicating activities or attributes of each participant in a group of multiple participants in a health research study, wherein the monitoring for each participant includes acquiring health data provided by an electronic device of the participant to the one or more computers over a communication network; 
 evaluating, by the one or more computers, the monitoring data for each of the participants in the group to predict readiness of the participants to receive one or more therapeutic interventions, including:
 deriving, for each participant, a set of scores from the monitoring data for the participant, the set of scores including values indicative of attributes or activities of the participant from monitoring data for the participant; and 
 generating, for each participant, output indicative of whether the participant is ready to receive the one or more therapeutic interventions, the output being generated by providing the set of scores to one or more models that have been configured to predict readiness of participants to receive a therapeutic intervention; 
 
 based on output of the one or more models, determining, by the one or more computers, whether the participants are respectively ready to receive the one or more therapeutic interventions; and 
 altering, by the one or more computers, interactions of the electronic devices with the participants to selectively provide therapeutic interventions in the health research study based on the determinations for the participants. 
   
     
     
         29 . The system of  claim 28 , wherein the group of participants is a cohort of participants for a clinical trial. 
     
     
         30 . The system of  claim 28 , wherein altering interactions with the participants comprises adjusting a frequency or type of health monitoring performed for one or more of the participants in the group. 
     
     
         31 . The system of  claim 28 , wherein the set of scores including values indicative of attributes or activities of the participant comprises value indicating physiological measurements for the participant or measures of behavior of the participant. 
     
     
         32 . The system of  claim 28 , wherein the one or more models are machine learning models that have been trained based on examples indicating attributes or activities of other participants and outcomes of providing the one or more therapeutic interventions to the other participants. 
     
     
         33 . The system of  claim 28 , wherein the operations further comprise generating a group readiness measure that provides an aggregate measure of readiness of the group of participants subjects for the one or more therapeutic interventions;
 wherein the interactions of the health research study that are provided through the electronic devices to the participants are based at least in part on the aggregate measure of readiness.   
     
     
         34 . The method of  claim 28 , wherein the operations further comprise using at least one model to predict likelihoods of completion of the health research study by the respective participants. 
     
     
         35 . One or more non-transitory computer-readable media storing instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:
 monitoring, by the one or more computers, data indicating activities or attributes of each participant in a group of multiple participants in a health research study, wherein the monitoring for each participant includes acquiring health data provided by an electronic device of the participant to the one or more computers over a communication network;   evaluating, by the one or more computers, the monitoring data for each of the participants in the group to predict readiness of the participants to receive one or more therapeutic interventions, including:
 deriving, for each participant, a set of scores from the monitoring data for the participant, the set of scores including values indicative of attributes or activities of the participant from monitoring data for the participant; and 
 generating, for each participant, output indicative of whether the participant is ready to receive the one or more therapeutic interventions, the output being generated by providing the set of scores to one or more models that have been configured to predict readiness of participants to receive a therapeutic intervention; 
   based on output of the one or more models, determining, by the one or more computers, whether the participants are respectively ready to receive the one or more therapeutic interventions; and   altering, by the one or more computers, interactions of the electronic devices with the participants to selectively provide therapeutic interventions in the health research study based on the determinations for the participants.   
     
     
         36 . The one or more non-transitory computer-readable media of  claim 35 , wherein the group of participants is a cohort of participants for a clinical trial. 
     
     
         37 . The one or more non-transitory computer-readable media of  claim 35 , wherein altering interactions with the participants comprises adjusting a frequency or type of health monitoring performed for one or more of the participants in the group. 
     
     
         38 . The one or more non-transitory computer-readable media of  claim 35 , wherein the set of scores including values indicative of attributes or activities of the participant comprises value indicating physiological measurements for the participant or measures of behavior of the participant. 
     
     
         39 . The one or more non-transitory computer-readable media of  claim 35 , wherein the one or more models are machine learning models that have been trained based on examples indicating attributes or activities of other participants and outcomes of providing the one or more therapeutic interventions to the other participants. 
     
     
         40 . The one or more non-transitory computer-readable media of  claim 35 , wherein the operations further comprise generating a group readiness measure that provides an aggregate measure of readiness of the group of participants subjects for the one or more therapeutic interventions;
 wherein the interactions of the health research study that are provided through the electronic devices to the participants are based at least in part on the aggregate measure of readiness.