Abstract: The disclosed system for testing of fleet management software generates virtual assets (e.g., simulations of machinery) that are associated with simulated sensor values. For at least one particular asset in the set, the system generates a simulated application programming interface (API) message definition structured to capture the simulated sensor values. The system binds the set of virtual assets to a simulation scenario record that includes a trigger condition. The system causes a scheduler to detect that the trigger condition is met, fetch the simulation scenario record, and generate simulated API messages for the assets according to the API message definitions.

Abstract: In one or more implementations, a method and system are disclosed in which at least one processor receives information associated with an upcoming arthroplasty and demographic factors of a patient in the upcoming arthroplasty. The processor(s) access i) procedure information representing arthroplasty previously performed for each of a plurality of patients and ii) implant information representing types and sizes of implants from a plurality of manufacturers. Further, the processor(s) determine respective unadjusted probabilities of each of a plurality of implant size options within a range of implant sizes, based on i) of at least one statistical model, ii) the accessed procedure information and the implant information, and iii) the demographic factors of the patient.

Abstract: In one or more implementations, a method and system are disclosed in which at least one processor receives information associated with an upcoming arthroplasty and demographic factors of a patient in the upcoming arthroplasty. The processor(s) access i) procedure information representing arthroplasty previously performed for each of a plurality of patients and ii) implant information representing types and sizes of implants from a plurality of manufacturers. Further, the processor(s) determine respective unadjusted probabilities of each of a plurality of implant size options within a range of implant sizes, based on i) of at least one statistical model, ii) the accessed procedure information and the implant information, and iii) the demographic factors of the patient.

Abstract: Generating a prediction for at least one implant size for use in arthroplasty is disclosed. Patient demographic factors are received and processed to generate at least one implant size prediction. The processing includes accessing procedure information representing joint replacement procedures previously performed for a plurality of patients and implant information representing types and sizes of implants from a plurality of manufacturers and determining, as a function of at least one statistical model and the accessed procedural information and implant information, unadjusted probabilities of implant size recommendations in a range of implant sizes. At least one processor is further configured for providing, in a graphical user interface operating on at least one user computing device, information representing the respective implant size recommendations and unadjusted probabilities.

Abstract: Generating a prediction for at least one implant size for use in arthroplasty is disclosed. Patient demographic factors are received and processed to generate at least one implant size prediction. The processing includes accessing procedure information representing joint replacement procedures previously performed for a plurality of patients and implant information representing types and sizes of implants from a plurality of manufacturers and determining, as a function of at least one statistical model and the accessed procedural information and implant information, unadjusted probabilities of implant size recommendations in a range of implant sizes. At least one processor is further configured for providing, in a graphical user interface operating on at least one user computing device, information representing the respective implant size recommendations and unadjusted probabilities.