Abstract: A system for helping a particular policy holder of a long term care insurance policy stay independent during a next year includes an external data gatherer, a model builder and an intervention determiner. The external data gatherer gathers claim data, and observation data of medical data and self-sufficiency data about a plurality of policy holders. The model builder builds a predictive model from features based on the claim data and the observation data and determines which of the policy holders are unlikely to remain independent during the next year. The intervention determiner determines, for a particular policy holder, an intervention to improve a probability that the particular policy holder remain independent for another year.

Abstract: A system for population health management to enable policy holders to defer long term care for the near term includes an external data gatherer, a model builder and an intervention determiner. The external data gatherer gathers data about a plurality of policy holders from at least two of medical records, direct observation, third party data sources, and questionnaires about lifestyles, family and caregivers. The model builder builds a model from at least one of scientifically based research and the gathered data and determines which of the policy holders are likely to claim for long term care in the near term. The intervention determiner determines, for a particular policy holder, at least one scientifically based intervention to improve a probability that the particular policy holder remain at home for another year.

Abstract: A method has a model predicting which elderly people are likely to claim for long term care (LTC) within a year based on long term care insurance claims of the elderly people and on assessment data of some of the elderly people. The method includes receiving living environment data of a particular senior with similar characteristics to the elderly people, which includes mobile device patterns of social activity, physical activity, phone use, shopping, sleeping, and waking by the particular senior, from the living environment data, determining a single feature of the features of the model whose change most likely reduces a probability of filing a claim for LTC within a period of time, providing to the particular senior a single intervention related to the single feature, and comparing further patterns of the particular senior with the previous patterns to determine an extent to which the particular senior implemented the intervention.

Abstract: A system for health management for policy holders to reduce disability in a long term. The system includes an external data gatherer, a model builder, a filterer and a plan selector. The external data gatherer gathers data about a plurality of policy holders from at least two of: medical records, wearable sensors, questionnaires about lifestyles, direct observations by professionals, family and caregivers, and third-party data sources. The model builder builds a health outcome model on the gathered data to generate probabilities of health outcomes and uses previously determined impact coefficients generated to determine the need for long term care in a near term. The filterer filters the probabilities to generate risk factors for a particular policy holder. The plan selector combines the risk factors with the gathered data and current incentive options to generate a health improvement plan for the particular policy holder.

Abstract: A system for population health management to enable policy holders to defer long term care for the near term includes an external data gatherer, a model builder and an intervention determiner. The external data gatherer gathers data about a plurality of policy holders from at least two of medical records, direct observation, third party data sources, and questionnaires about lifestyles, family and caregivers. The model builder builds a model from at least one of scientifically based research and the gathered data and determines which of the policy holders are likely to claim for long term care in the near term. The intervention determiner determines, for a particular policy holder, at least one scientifically based intervention to improve a probability that the particular policy holder remain at home for another year.

Abstract: A method of establishing a connection among a plurality of persons according to embodiments of the present invention may include executing instructions by a processor to identify a characteristic that is present in a first image of a portfolio of images and in a second image of the portfolio of images; defining by the characteristic an association of the first image and the second image; and defining a social connection between a first person associated with the first image and a second person associated with the second image. According to some embodiments, a method of identifying a connection between a first person and a second person, may include: receiving, by a computing device, at least one image that may include a data characteristic associated with the first person and with the second person; automatically identifying that the at least one image includes the characteristic; and automatically associating the first person and the second person.

Abstract: Embodiments of the invention include a method of predicting that a person appearing in an image is an operator of a device capturing the image. Embodiments of the method include designating a first person appearing in a first image stored in a storage-unit associated with the device and designating a second person appearing in a second image stored in the storage-unit. Embodiments of the method further include calculating a first probability that the first person is the operator of the device, calculating a second probability that the second person is the operator of the device and comparing the first probability to the second probability.

Abstract: A method of controlling an electronic device thought, includes: capturing through one or more electrodes, located in proximity to a brain of a user, signals of brainwave activity of said user; analyzing said signals to detect a pattern of brainwave activity of said user; based on the detected pattern, determining that the user thinks about a command that controls an electronic device; and based on said determining, triggering the electronic device to perform said command.

Abstract: A method for determining that a user associated with a first identifiable device or identifiable service is also associated with a second identifiable device or identifiable service by a) generating one or more first image descriptors for one or more first images stored on the first identifiable service associated with a first user, b) generating one or more second image descriptors for one or more second images stored on the second identifiable service associated with a second user, c) calculating, based on the generated first and second image descriptors, the probability that the first user is also the second user. Also provided is a computer readable storage medium containing program code for implementing the method.

Abstract: A method of generating user insights based on one or more user images and one or more other data is provided, including receiving one or more image files on an identifiable device or service, receiving at least one of image metadata or identifiable device or service metadata, analyzing features of the received image files, based on at least one of the received image metadata or identifiable device or service metadata and generating at least one user insight for a user associated with the identifiable device or service. Also provided is a computer readable storage medium containing program code for implementing the method.

Abstract: A method for determining that a user associated with a first identifiable device or identifiable service is also associated with a second identifiable device or identifiable service by a) generating one or more first image descriptors for one or more first images stored on the first identifiable service associated with a first user, b) generating one or more second image descriptors for one or more second images stored on the second identifiable service associated with a second user, c) calculating, based on the generated first and second image descriptors, the probability that the first user is also the second user. Also provided is a computer readable storage medium containing program code for implementing the method.

Abstract: A method of generating user insights based on one or more user images and one or more other data is provided, including receiving one or more image files on an identifiable device or service, receiving at least one of image metadata or identifiable device or service metadata, analyzing features of the received image files, based on at least one of the received image metadata or identifiable device or service metadata and generating at least one user insight for a user associated with the identifiable device or service. Also provided is a computer readable storage medium containing program code for implementing the method.

Abstract: A method for determining a user's identifier on an identifiable service by: a) capturing a user action performed by the user on a first identifiable service where the user action causes user generated content to be added to a second identifiable service; b) monitoring the second identifiable service for events of user generated content being added to the second identifiable service by users of the second identifiable service, each such event of user generated content being associated with a user identifier, and recording the event and the respective user identifier; c) determining a probabilistic match between the captured user action and one of the one or more monitored events. Also provided is a computer readable storage medium containing program code for implementing the method.