Systems and methods for automated customized cohort communication

Abstract

Systems and methods for feature-based alert triggering are disclosed herein. The system can include memory including a model database containing a machine-learning algorithm. The system can include a user device that can receive inputs from a user; and at least one server. The at least one server can: receive electrical signals from the user device, the electrical signals corresponding to a plurality of user inputs provided to the user device; automatically generate input-based features from the received electrical signals; input the input-based features into the machine-learning algorithm; automatically and directly generate a risk prediction with the machine-learning algorithm from the input-based features; and generate and display an alert when the risk prediction exceeds a threshold value.

What is claimed is: 
     
         1 . A system for automated customized cohort communication, the system comprising:
 memory comprising:   a user database comprising information identifying a plurality of users and communication information associated with each of the plurality of users, wherein a risk status is associated with each of the plurality of users;   a first user device configured to receive inputs from a first user;   a second user device configured to receive inputs from a second user;   a third user device; and   at least one server configured to:
 receive communications corresponding to a plurality of user inputs provided to the first user device and the second user device; 
 generate a first risk prediction for the first user with a machine-learning algorithm and a second risk prediction for the second user with the machine-learning algorithm, wherein the first and second risk predictions are based on features generated from the received communications; 
 determine inclusion of the first risk prediction in a first cohort associated with a first risk level and a second risk prediction in a second cohort associated with a second risk level; 
 direct generation of a user interface on the third user device, the user interface comprising a graphical depiction of the first and second cohorts; 
 receive a communication request from the third user device; 
 identify a recipient cohort comprising at least one user associated with the communication request; 
 automatically retrieve communication information for each of the at least one user of the recipient cohort; and 
 send a communication to each of the at least one user of the recipient cohort according to the communication information. 
   
     
     
         2 . The system of  claim 1 , wherein the recipient cohort comprises the first cohort associated with the first risk level. 
     
     
         3 . The system of  claim 1 , wherein the recipient cohort comprises the first cohort associated with the first risk level and the second cohort associated with the second risk level. 
     
     
         4 . The system of  claim 3 , wherein the communication is sent to at least the first user device and the second user device. 
     
     
         5 . The system of  claim 3 , further comprising a fourth user device, wherein the fourth user device is linked to the second user in the user database. 
     
     
         6 . The system of  claim 5 , wherein the communication is sent to at least the first user device and the fourth user device. 
     
     
         7 . The system of  claim 1 , wherein the at least one server is further configured to receive communication content and a recipient cohort modification. 
     
     
         8 . The system of  claim 7 , wherein the recipient cohort modification adds at least another user to recipient cohort for receipt of the communication. 
     
     
         9 . The system of  claim 7 , wherein the recipient cohort modification removes at least one user from the recipient cohort. 
     
     
         10 . The system of  claim 1 , wherein generating the first risk prediction based on features generated from the received communications comprises: generating a feature vector for each of the features; and inputting the feature vectors into the machine-learning algorithm. 
     
     
         11 . A method for automated customized cohort communication, the method comprising:
 receiving communications corresponding to a plurality of user inputs provided to a first user device by a first user and to a second user device by a second user;   generating a first risk prediction for the first user with a machine-learning algorithm and a second risk prediction for the second user with the machine-learning algorithm, wherein the first and second risk predictions are based on features generated from the received communications;   determining inclusion of the first risk prediction in a first cohort associated with a first risk level and a second risk prediction in a second cohort associated with a second risk level;   directing generation of a user interface on a third user device, the user interface comprising a graphical depiction of the first and second cohorts;   receiving a communication request from the third user device;   identifying a recipient cohort comprising at least one user associated with the communication request;   automatically retrieving communication information for each of the at least one user of the recipient cohort; and   sending a communication to each of the at least one user of the recipient cohort according to the communication information.   
     
     
         12 . The method of  claim 11 , wherein the recipient cohort comprises the first cohort associated with the first risk level. 
     
     
         13 . The method of  claim 11 , wherein the recipient cohort comprises the first cohort associated with the first risk level and the second cohort associated with the second risk level. 
     
     
         14 . The method of  claim 13 , wherein the communication is sent to at least the first user device and the second user device. 
     
     
         15 . The method of  claim 13 , wherein the communication is sent to at least the first user device and a fourth user device. 
     
     
         16 . The method of  claim 15 , wherein the fourth user device is linked to the second user in a user database comprising information identifying a plurality of users and communication information associated with each of the plurality of users. 
     
     
         17 . The method of  claim 11 , further comprising receiving communication content and a recipient cohort modification. 
     
     
         18 . The method of  claim 17 , wherein the recipient cohort modification adds at least another user to recipient cohort for receipt of the communication. 
     
     
         19 . The method of  claim 17 , wherein the recipient cohort modification removes at least one user from the recipient cohort. 
     
     
         20 . The method of  claim 11 , wherein generating the first risk prediction based on features generated from the received communications comprises: generating a feature vector for each of the features; and inputting the feature vectors into the machine-learning algorithm.