Abstract: Methods, systems, and computer-readable media are disclosed herein for generating, training, and deploying a specialized data model that is accessible through a computer software application for clinical decision support. Through the application and data model, a particular set of vaccine formulations for treating or preventing a condition are identified, the data model having a deep knowledge of the contraindications of each vaccine formulation. Using an individual-specific electronic record, data values are extracted by the application and used by the data model to determine whether a conflict is identifiable between the data values and the complex and varied contraindications of each vaccine formulation. The application preferentially presents conflict-free formulations as recommendation for administration to an individual that corresponds to the individual-specific electronic record and omits/prevents the display for those formulations having a conflict in a graphical user interface.

Abstract: Methods, systems, and computer-readable media are disclosed herein for intelligently identifying specific timeslots and identifying specific durations for the timeslots that can be recommended to a person seeking to make an appointment with a clinician. A scheduling module leverages real-time GPS data of the person and clustering techniques to identify the timeslots and predicted durations the person is predicted to utilize in that appointment based at least on a chief complaint and patient cohort data.

Abstract: Methods, systems, and computer-readable media are disclosed herein for providing objective electronic medical record (EMR) system adoption analysis. In an aspect, a subjective input and an objective input is received by a user via a user computing device. The subjective input is comprised of at least one of knowledge assessment related to an EMR system, an attitude assessment related to the EMR system, or a practice assessment related to the EMR system. The objective input is comprised of demographic data related to the user of the EMR system. A score is then calculated for the objective and subjective input, wherein calculating the score comprises applying a weight to the objective and the subjective input to determine one or more of a knowledge score, an attitude score, or a practice score. It is determined that at least one of the knowledge score, attitude score, or practice score, is below at least one predetermined threshold.

Abstract: Methods, systems, and computer-readable media are disclosed herein for automated identification and alerting of neurodegenerative diseases (NDD). Patient information comprising medical history information is accessed. Using the patient information, one or more risk factors and/or symptoms for a NDD are identified. Using the identified risk factors and/or symptoms, a patient with probable risk for developing the NDD is determined. A notification of the probable risk that the patient develops the NDD is provided.

Abstract: Methods, systems, and computer-readable media are disclosed herein for automated susceptibility identification and alerting. An occurrence of an outbreak of an infectious disease occurring at a particular time or time range and at a particular location is determined. In response to determining the occurrence of the outbreak, patient information comprising location information and medical history information is automatically scanned. Patients who are within a predetermined range of the particular location of the outbreak and who have at least one high risk factor corresponding to the outbreak are identified using the patient information. A notification to at least one of the patients who are within the predetermined range and who have the at least one high risk factor corresponding to the outbreak is provided. The notification comprises a representation of an increased risk to the outbreak.

Abstract: The present subject matter discloses systems and methods package material modeling in an enterprise. The method includes computing stress values and strain values utilizing input data. The method further includes generating a primary material model utilizing the stress values and the strain values, wherein the primary material model is indicative of the material behavior characteristics. Furthermore, the method includes estimating a coefficient of error and a trend factor; wherein the coefficient of error is indicative of error in the primary material model, wherein the trend factor is indicative of the trend in difference between historical data and the primary material model.

Abstract: In one embodiment, a multiwall sheet comprises a first sheet comprising an inner surface and an outer surface, a second sheet comprising a first surface and a second surface; and a rib disposed between the inner surface and the first surface. The outer layer can have surface features and has a surface area of greater than or equal to 140% of a planar, flat, non-profiled surface area for a same unit area.

Abstract: In one embodiment, a multiwall sheet comprises a first sheet comprising an inner surface and an outer surface, a second sheet comprising a first surface and a second surface; and a rib disposed between the inner surface and the first surface. The outer layer can have surface features and has a surface area of greater than or equal to 140% of a planar, flat, non-profiled surface area for a same unit area.