How VitaliSee Works
VitaliSee has pioneered a new deep-learning AI approach by taking the human orthopedic narrative and converting it into a mathematical prediction formula using data-driven guidance. By using this breakthrough deep-learning AI method, VitaliSee enables unprecedented TIME-TO-EVENT forecasting accuracy through the ability to use machine learning on highly disparate data.
Embracing Data Realities
VitaliSee is input agnostic—learning from any data source available to the practitioner—including biomarkers from electronic health records, performance derivatives from conventional monitoring practices, wearable devices, psychological and survey data, and more. Through a strategic alliance with SPEAR, data sets are stored and protected by Impact Level 5 (IL5) security—the U.S. Department of Defense’s most stringent security requirements—to exceed HIPPA and other regulatory requirements.
By leveraging the power of deep-learning neural networks on disparate data, VitaliSee discovers the hidden, innate relationships amongst data elements while taking away the error prone and time consuming task of manual data formatting. VitaliSee develops a network for each individual observational unit based on the relationships discovered within its training. That object’s network continues to evolve as the data related to that object evolves and updates. In layman’s terms, VitaliSee creates an individualized, time-to-event forecast that dynamically evolves as the individual’s environment and data evolves.
See how VitaliSee accurately predicts who’s going to suffer a musculoskeletal injury (MSK-I) and when the injury was going to occur within a very limited, Time-to-Event data set.
