Abstract: Techniques for generating an ontology based on biomarker information associated with persons to facilitate improving clinical predictions relating to medical conditions are presented. An ontology generator component (OGC) can extract clinical features associated with patients and their associated times from medical records or databases to develop clinical profiles associated with the patients and relating to a medical condition. OGC can develop an ontology relating to the medical condition, including progression and severity of biomarkers associated with the medical condition, based on the clinical profiles and domain knowledge information relating to the medical condition. OGC can determine global features relating to progression and severity associated with the medical condition based on the ontology. At a forecasting point, the global features can be extracted from the ontology and applied to a prediction model to enhance prediction of onset of, or progression of, the medical condition for a patient.

Abstract: A processor may receive data associated with one or more users regarding biomarkers for a condition. The processor may determine one or more progression trajectories from the data using progression modeling. The processor may identify one or more granular stages associated with the one or more progression trajectories. The processor may generate a risk assessment for development of the condition associated with the one or more progression trajectories and the one or more granular stages.

Abstract: Techniques facilitating autoimmune disorder screening schedule evaluations. In one example, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise a pre-processing component and an evaluation component. The pre-processing component can generate a biomarker dataset for a subpopulation using an aggregated database of biomarker data for a population comprising the subpopulation. The evaluation component can determine a performance metric for a screening schedule based on the biomarker dataset. The performance metric can quantify an effectiveness of the screening schedule in identifying subjects within the subpopulation that are at risk of developing an autoimmune disorder.

Abstract: A method and system for preventing falls and accidents is provided comprising. A user's location and movement are monitored by a number of input devices. The user's activities are also monitored by a number of input devices. Potential dangers are identified within a first specified proximity of the user, and a determination is made if the user's current activity indicates a cognitive load that exceeds a predefined threshold. In response to identification of a potential danger within the first specified proximity and a concurrent determination that the user's cognitive load exceeds the threshold, a number of devices within a second specified proximity of the user are activated to alert the user of the potential danger.

Abstract: A shipment sharing method, system, and computer program product include collecting a shopping order history, neighborhood information and friends' information from user data, analyzing a current order by a user from a shopping service, checking whether a neighbor identified from the neighborhood information and the friend information purchased an item from the shopping service based on the shopping order history, and suggesting to the user to share a packing and shipment cost with the neighbor by combining the purchased one or more items by the neighbor and the current order by the user in a single package.

Abstract: A method and system for preventing falls and accidents is provided comprising. A user's location and movement are monitored by a number of input devices. The user's activities are also monitored by a number of input devices. Potential dangers are identified within a first specified proximity of the user, and a determination is made if the user's current activity indicates a cognitive load that exceeds a predefined threshold. In response to identification of a potential danger within the first specified proximity and a concurrent determination that the user's cognitive load exceeds the threshold, a number of devices within a second specified proximity of the user are activated to alert the user of the potential danger.