Abstract: A data collection system that provides the means to collect, store and make data available for a location analytics inference pipeline. The system incorporates a feedback mechanism enabling algorithms produced from the inference pipeline to drive the collection strategy to yield higher data quality and to produce reference data for model validation.

Abstract: Aspects of the inventive concepts involve a system and a method that include or use an AI overlay that applies models to interpret content from an electronic health record (EHR) display and generate insights related to the displayed EHR. Healthcare practices access an EHR system comprising a plurality of patient EHRs. The practice also has access to an application linked to at least one secondary source of patient information, such as an accountable care organization (ACO) application. The AI overlay implements vision or image-based processing of a displayed patient EHR to generate the insights from the secondary source of patient information, such as a summary of relevant patient data created since the patient's last visit to the practice (e.g., payer claims, pharmacy and lab information, admission, discharge and transfer events), and to provide auxiliary information, such as potential diagnosis and/or suggested care actions, within the screen displaying the EHR.

Abstract: A system to infer place data is disclosed that receives location data collected on a user's mobile electronic device, recognizes when, where and for how long the user makes stops, generates possible places visited, and predicts the likelihood of a user to visit those places.

Abstract: A system to infer place data is disclosed that receives location data collected on a user's mobile electronic device, recognizes when, where and for how long the user makes stops, generates possible places visited, and predicts the likelihood of a user to visit those places.

Abstract: A system and method for attributing in-store visits to exposure to advertisement (“ad”) impressions associated with an ad campaign are disclosed. The system gathers impression data and uses that data to identify users who were exposed to the ad impressions. The system then uses location data, activity information and in some instances beacon data points reported by mobile devices of the impression users to determine if the impression users visited a target place during a conversion window. Based on the impression users who were exposed to the ad impressions, the system establishes a control group of users who were not exposed to the ad impressions to perform quasi-experimental analyses to assess whether the ad impressions had any impact on changing the impression users' physical in-store visitation behavior.

Abstract: A targeting system based on a predictive targeting model based on observed behavioral data including visit data, user profile and/or survey data, and geographic features associated with a geographic region. The predictive targeting model analyzes the observed behavioral data and the geographic features data to predict conversion rates for every cell in a square grid of predefined size on the geographic region. The conversion rate of a cell indicates a likelihood that any random user in that cell will perform a targeted behavior.

Abstract: A system and method for attributing in-store visits to exposure to advertisement (“ad”) impressions associated with an ad campaign are disclosed. The system gathers impression data and uses that data to identify users who were exposed to the ad impressions. The system then uses location data, activity information and in some instances beacon data points reported by mobile devices of the impression users to determine if the impression users visited a target place during a conversion window. Based on the impression users who were exposed to the ad impressions, the system establishes a control group of users who were not exposed to the ad impressions to perform quasi-experimental analyses to assess whether the ad impressions had any impact on changing the impression users' physical in-store visitation behavior.

Abstract: A targeting system based on a predictive targeting model based on observed behavioral data including visit data, user profile and/or survey data, and geographic features associated with a geographic region. The predictive targeting model analyzes the observed behavioral data and the geographic features data to predict conversion rates for every cell in a square grid of predefined size on the geographic region. The conversion rate of a cell indicates a likelihood that any random user in that cell will perform a targeted behavior.

Abstract: A data collection system that provides the means to collect, store and make data available for a location analytics inference pipeline. The system incorporates a feedback mechanism enabling algorithms produced from the inference pipeline to drive the collection strategy to yield higher data quality and to produce reference data for model validation.

Abstract: A data collection system that provides the means to collect, store and make data available for a location analytics inference pipeline. The system incorporates a feedback mechanism enabling algorithms produced from the inference pipeline to drive the collection strategy to yield higher data quality and to produce reference data for model validation.

Abstract: A targeting system based on a predictive targeting model based on observed behavioral data including visit data, user profile and/or survey data, and geographic features associated with a geographic region. The predictive targeting model analyzes the observed behavioral data and the geographic features data to predict conversion rates for every cell in a square grid of predefined size on the geographic region. The conversion rate of a cell indicates a likelihood that any random user in that cell will perform a targeted behavior.

Abstract: A data collection system that provides the means to collect, store and make data available for a location analytics inference pipeline. The system incorporates a feedback mechanism enabling algorithms produced from the inference pipeline to drive the collection strategy to yield higher data quality and to produce reference data for model validation.

Abstract: A system to infer place data is disclosed that receives location data collected on a user's mobile electronic device, recognizes when, where and for how long the user makes stops, generates possible places visited, and predicts the likelihood of a user to visit those places.

Abstract: A system to infer place data is disclosed that receives location data collected on a user's mobile electronic device, recognizes when, where and for how long the user makes stops, generates possible places visited, and predicts the likelihood of a user to visit those places.

Abstract: A system to infer place data is disclosed that receives location data collected on a user's mobile electronic device, recognizes when, where and for how long the user makes stops, generates possible places visited, and predicts the likelihood of a user to visit those places.

Abstract: A targeting system based on a predictive targeting model based on observed behavioral data including visit data, user profile and/or survey data, and geographic features associated with a geographic region. The predictive targeting model analyzes the observed behavioral data and the geographic features data to predict conversion rates for every cell in a square grid of predefined size on the geographic region. The conversion rate of a cell indicates a likelihood that any random user in that cell will perform a targeted behavior.

Abstract: A system and method for attributing in-store visits to exposure to advertisement (“ad”) impressions associated with an ad campaign are disclosed. The system gathers impression data and uses that data to identify users who were exposed to the ad impressions. The system then uses location data, activity information and in some instances beacon data points reported by mobile devices of the impression users to determine if the impression users visited a target place during a conversion window. Based on the impression users who were exposed to the ad impressions, the system establishes a control group of users who were not exposed to the ad impressions to perform quasi-experimental analyses to assess whether the ad impressions had any impact on changing the impression users' physical in-store visitation behavior.

Abstract: A system to infer place data is disclosed that receives location data collected on a user's mobile electronic device, recognizes when, where and for how long the user makes stops, generates possible places visited, and predicts the likelihood of a user to visit those places.

Abstract: A data collection system that provides the means to collect, store and make data available for a location analytics inference pipeline. The system incorporates a feedback mechanism enabling algorithms produced from the inference pipeline to drive the collection strategy to yield higher data quality and to produce reference data for model validation.

Abstract: A system to infer place data is disclosed that receives location data collected on a user's mobile electronic device, recognizes when, where and for how long the user makes stops, generates possible places visited, and predicts the likelihood of a user to visit those places.