Machine-learning for state determination and prediction
AssigneeOptum Services (Ireland) Limited
InventorsDamian Kelly, Dominik Dahlem, Rick Hamilton
Life of this patent
Estimating the term…
Abstract
Without timely reminders, certain individuals may be highly unlikely to complete various tasks scheduled for completion. For example, medicinal therapy regimen patients often have difficulty in remembering to take their prescribed medications in accordance with care provider specified instructions. By providing a reminder prompt generation system that utilizes machine-learning and/or artificial intelligence to determine appropriate reminder times and modalities for providing automated-prompting notifications to users, the users' adherence to scheduled task completions can be significantly increased.
Claims27
An apparatus comprising at least one processor and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following:
- store a schedule comprising a task to be performed by a user;
- provide a first automated-prompting notification to the user to perform the task;
- determine that the user completed the task responsive to the first automated-prompting notification, wherein (a) a first state of the user and a first state of the user's environment are stored in association with the first automated-prompting notification, (b) the first state of the user, the first state of the user's environment, and the first automated-prompting notification are used to train a prompting model using machine learning, and (c) the prompting model outputs one or more automated-prompting notifications;
- detect a first input indicative of a context of an environment of the user;
- detect a first input indicative of a context of the user;
- determine, based at least in part on the first input indicative of the context of the environment of the user and the first input indicative of the context of the user, a second state of the user and a second state of the user's environment;
- determine, based at least in part on the second state of the user, the second state of the user's environment, and the prompting model, a second automated-prompting notification;
- and
- provide the second automated-prompting notification.
A method for providing automated-prompting notifications for a user, the method comprising:
- storing, via a non-transitory memory storage area, a schedule comprising a task to be performed by a user;
- providing, via one or more processing devices, a first automated-prompting notification to the user to perform the task;
- determining, via the one or more processing devices, that the user completed the task responsive to the first automated-prompting notification, wherein (a) a first state of the user and a first state of the user's environment are stored in association with the first automated-prompting notification, (b) the first state of the user, the first state of the user's environment, and the first automated-prompting notification are used to train a prompting model using machine learning, and (c) the prompting model outputs one or more automated-prompting notifications;
- detecting, via the one or more processing devices, a first input indicative of a context of an environment of the user;
- detecting, via the one or more processing devices, a first input indicative of a context of the user;
- determining, via the one or more processing devices and based at least in part on the first input indicative of the context of the environment of the user and the first input indicative of the context of the user, a second state of the user and a second state of the user's environment;
- determining, via the one or more processing devices and based at least in part on the second state of the user, the second state of the user's environment, and the prompting model, a second automated-prompting notification;
- and
- providing, via the one or more processing devices, the second automated-prompting notification.
A computer program product comprising a non-transitory computer readable medium having computer program instructions stored therein, the computer program instructions when executed by a processor, cause the processor to:
- store a schedule comprising a task to be performed by a user;
- provide a first automated-prompting notification to the user to perform the task;
- determine that the user completed the task responsive to the first automated-prompting notification, wherein (a) a first state of the user and a first state of the user's environment are stored in association with the first automated-prompting notification, (b) the first state of the user, the first state of the user's environment, and the first automated-prompting notification are used to train a prompting model using machine learning, and (c) the prompting model outputs one or more automated-prompting notifications;
- detect a first input indicative of a context of an environment of the user;
- detect a first input indicative of a context of the user;
- determine, based at least in part on the first input indicative of the context of the environment of the user and the first input indicative of the context of the user, a second state of the user and a second state of the user's environment;
- determine, based at least in part on the second state of the user, the second state of the user's environment, and the prompting model, a second automated-prompting notification;
- and
- provide the second automated-prompting notification.
Dependencies are inferred from the claim text.