The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

The present disclosure relates to systems and methods for matching electronic activities with record objects based on entity relationships. The method can include accessing a plurality of electronic activities, identifying an electronic activity, identifying a first participant associated with a first entity and a second participant associated with a second entity, determining whether a record object identifier is included in the electronic activity, identifying a first record object of the system of record that includes an instance of the record object identifier, and storing an association between the electronic activity and the first record object. The method can include determining a second record object corresponding to the second entity, identifying, using a matching policy, a third record object linked to the second record object and identifying a third entity, and storing, by the one or more processors, an association between the electronic activity and the third record object.

The present invention relates to a system for providing genetic information-based personalized social content information, and a method thereof. Disclosed, according to one embodiment, is a system for providing genetic information-based personalized social content information, the system comprising: a genetic testing device unit which performs genetic testing for genetic physical characteristics and genetic disorders of a user; a solution management item provision unit which is installed in a management server, receives a genetic testing result as input from the genetic testing device unit, and, according to the inputted genetic testing result, provides solution management items including improvement methods for and worsening factors of the genetic physical characteristics and genetic disorders of the user; a solution performance checking unit which is installed in a communication terminal of the user, receives, from the user, inputs on whether each of the solution management items, provided by the solution management item provision unit, have been performed, and transmits same to the outside at every predetermined time period; and a user management state analysis and management unit which is installed in the management server, and analyzes and manages the degree of improvement and worsening of the genetic physical characteristics and genetic disorders of the user, according to results on whether the solution management items have been performed, which are received from the solution performance checking unit.

The present disclosure relates to a system for providing customized cosmetics by using genetic information, the system comprising: a terminal that receives user information related to a user; a genetic/medical information server that stores genetic information related to the user; a skin meter that acquires skin information on the user; and a cosmetic manufacturing system that manufactures cosmetics by discharging at least one cosmetic material, wherein the cosmetic manufacturing system can select a cosmetic material to be discharged on the basis of at least one among the user information, the genetic information, and the skin information.

A processing unit includes a contribution-degree calculation unit configured to calculate contribution degrees that indicate respective degrees by which a plurality of attribute items included as predetermined attributes of one target contribute to a predicted intervention effect, the calculating being performed on a basis of an estimation model for estimating the predicted intervention effect from the predetermined attributes of the one target. The predicted intervention effect on the one target is a numerical value corresponding to an increase in gain to a beneficiary, the gain being expected to be larger in a case where an intervention is implemented to the one target than in a case where the intervention is unimplemented to the one target.

The instant invention relates to a system that in one form is a referral system for use in various healthcare sectors, which utilizes patient profiles, created using patient trackers, to monitor patient follow-up care. The instant invention allows physicians and providers to communicate about patient’s care in its entirety, beginning with the originating provider creating a patient tracker, sharing that patient tracker with referred physicians, and discharging the patient once the patient tracker’s plans have concluded. This uninterrupted flow of communication amongst all providers and physicians allows for a secured method of tracking each patient’s healthcare plan, provides for efficient healthcare referral follow-ups, and updates the originating HCPs records to ensure there are no gaps in terms of patient treatment.

Methods, apparatus, systems, computing devices, computing entities, and/or the like for using machine-learning concepts (e.g., machine learning models) to determine predicted taxonomy-based classification scores for claims and dynamically update data fields based on the same.

Systems and methods may be used to predict an applicable a hearing assistance device shell or model. For example, a method may include obtaining patient information, determining, using a machine learning trained model, a correlation between an input vector and each of a plurality of feature vectors corresponding to a plurality of hearing assistance device models, and ranking the plurality of hearing assistance device models based on respective correlations to the input vector. Information corresponding to a highest ranked hearing assistance device model may be output.

A method including generating, by a state engine from data describing behaviors of users in an environment external to the state engine, an executable process. An agent executes the executable process by determining, from the data describing the behaviors of the users, a problem of at least some of the users, and selects, based on the problem, a chosen action to alter the problem. At a first time, a first electronic communication describing the chosen action to the at least some of the users is transmitted. Ongoing data describing ongoing behaviors of the users is monitored. A reward is generated based on the ongoing data to change a parameter of the agent. The parameter of the agent is changed to generate a modified agent. The modified agent executes the executable process to select a modified action. At a second time, a second electronic communication describing the modified action is transmitted.

Methods and systems for classifying and editing insurance claims records are described. In one embodiment, a method, which can be performed by a processor, includes determining that a first prescription drug prescribed to a first patient should be filled by a pharmacy, determining a first guidepost date and a second guidepost date related to the first prescription, determining a third guidepost date associated with a second prescription, comparing the third guidepost date to the first and second guidepost dates to determine whether the third guidepost date occurs after the first guidepost date and before the second guidepost date, and filling and dispensing the first prescription drug as a full prescription supply and the second prescription drug as a full prescription supply on the same dispense date when the third guidepost date occurs after the first guidepost date and before the second guidepost date.