Abstract: Embodiments of the present invention provide methods, computer program products, and a system for determining and providing health risk alerts. Embodiments of the present invention can be used to collect numbers entered by a user, which in turn are used to determine the health risks of the behavior of the user. Embodiments of the present invention can be used to issue alerts to a person of interest based, at least in part, on the number strings entered by the user.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a healthcare analytics management system. A healthcare analytics development sub-system of the healthcare analytics management system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. The healthcare analytics model links to the analytics pipeline. A model deployment module of a healthcare analytics operation sub-system of the healthcare analytics management system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer.

Abstract: A mechanism is provided in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a healthcare analytics management system. A healthcare analytics development sub-system of the healthcare analytics management system develops an analytics pipeline of a set of analytics assets for a selected healthcare based on a set of business needs for a healthcare analytics client and a healthcare analytics model based on the set of analytics assets and the set of business needs. The healthcare analytics model links to the analytics pipeline. A model deployment module of a healthcare analytics operation sub-system of the healthcare analytics management system deploys the healthcare analytics model on a set of computing devices of the selected healthcare consumer.

Abstract: Individual health vulnerability is assessed by obtaining health risk prevalence level data containing health risk prevalence levels for one or more health risks over a given geographical area. The health risk prevalence level data to generate for each health risk a prevalence level forecast as a function of time and location. A health risk prevalence level map is generated for the given geographical area illustrating current and future health risk prevalence levels for each health risk at a plurality of locations within the given geographical area. Personal health status data are obtained for a given individual along with a proposed travel itinerary f covering at least a portion of the geographical area over a given time duration. The personal health status data, travel itinerary and map generate a personal health risk vulnerability model containing a quantification of vulnerability to the one or more health risks resulting from the travel itinerary.

Abstract: Individual health vulnerability is assessed by obtaining health risk prevalence level data containing health risk prevalence levels for one or more health risks over a given geographical area. The health risk prevalence level data to generate for each health risk a prevalence level forecast as a function of time and location. A health risk prevalence level map is generated for the given geographical area illustrating current and future health risk prevalence levels for each health risk at a plurality of locations within the given geographical area. Personal health status data are obtained for a given individual along with a proposed travel itinerary f covering at least a portion of the geographical area over a given time duration. The personal health status data, travel itinerary and map generate a personal health risk vulnerability model containing a quantification of vulnerability to the one or more health risks resulting from the travel itinerary.

Abstract: Individual health vulnerability is assessed by obtaining health risk prevalence level data containing health risk prevalence levels for one or more health risks over a given geographical area. The health risk prevalence level data to generate for each health risk a prevalence level forecast as a function of time and location. A health risk prevalence level map is generated for the given geographical area illustrating current and future health risk prevalence levels for each health risk at a plurality of locations within the given geographical area. Personal health status data are obtained for a given individual along with a proposed travel itinerary f covering at least a portion of the geographical area over a given time duration. The personal health status data, travel itinerary and map generate a personal health risk vulnerability model containing a quantification of vulnerability to the one or more health risks resulting from the travel itinerary.

Abstract: Individual health vulnerability is assessed by obtaining health risk prevalence level data containing health risk prevalence levels for one or more health risks over a given geographical area. The health risk prevalence level data to generate for each health risk a prevalence level forecast as a function of time and location. A health risk prevalence level map is generated for the given geographical area illustrating current and future health risk prevalence levels for each health risk at a plurality of locations within the given geographical area. Personal health status data are obtained for a given individual along with a proposed travel itinerary f covering at least a portion of the geographical area over a given time duration. The personal health status data, travel itinerary and map generate a personal health risk vulnerability model containing a quantification of vulnerability to the one or more health risks resulting from the travel itinerary.

Abstract: Aspects of the present invention include a method, system and computer program product. The method includes identifying, by a processor, a set of global risk factors for a target event using training patients, and providing, by the processor, a disease progression timeline with defined time stamps by aligning longitudinal data of the training patients based on the defined time stamp of risk targets. The method also includes positioning, by the processor, a target patient at one of the defined time stamps on the disease progression timeline, and identifying, by the processor, at least one of the training patients similar to the target patient with the same one of the defined time stamps on the disease progression timeline. The method further includes calculating, by the processor, a time-varying predictive pattern of at least a portion of the global set of risk factors for the target patient along the disease progression timeline.

Abstract: A method and system for time varying risk profiling from sensor data includes receiving data time series from a plurality of sensors associated with a single patient, identifying events from the data, wherein an event is a transition between two states in the data of a sensor, formulating event prediction as a discrete state transition task using Markov jump processes to handle irregular sampling rates, estimating a transition density function for time varying continuous event probability using a hierarchical Bayesian model, and predicting risk events for the single patient by applying the hierarchical Bayesian model.

Abstract: A microfluidic system-on-a-chip includes signal processing, light generation and detection, and fluid handling functions formed on a single substrate. The disclosed integrated system has a smaller footprint than device structures where individual components are manufactured separately and then assembled. Moreover, the integrated system obviates alignment challenges associated with conventionally packaged architecture.

Abstract: In one embodiment, a computer-implemented method includes transforming a plurality of electronic health records into a plurality of temporal graphs indicating an order in which events observed in the plurality of electronic health records occur and learning a temporal pattern from the plurality of temporal graphs, wherein the temporal pattern indicates an order of events that is observed to occur repeatedly across the plurality of temporal graphs.

Abstract: Purified therapeutic nanoparticles are provided herein. Such nanoparticles comprise an active pharmaceutical ingredient and human serum albumin, wherein the weight ratio of human serum albumin to the active ingredient in the therapeutic nanoparticles is from 0.01:1 to 1:1, and wherein the nanoparticles are substantially free of free human serum albumin that is not incorporated in the nanoparticles. The present disclosure also provides pharmaceutical compositions that comprise the purified therapeutic nanoparticles and are also substantially free of free human serum albumin. Methods for preparing and using the purified therapeutic nanoparticles and compositions thereof are also provided.