SoarTech hasn’t always focused on medical, however while solving many of the military’s toughest problems in other domains, we’ve been able to pull in expertise and apply many solutions into the medical domain. We encourage a cyclical mindset of development so when we identify something in the training domain that can be translated to a solution for the operational environment, we act on it. Leveraging our experience allows us to integrate intelligent training capabilities into operational systems, and rich data from the operational environment allows us to refine our system(s) and improve the feedback, which allows us to evolve to meet our users’ needs.
Our team has a wide range of education and experience, from human factors to AEP, as well as hospital practitioners experienced in the robotic surgery domain. The team brings a robust and unique perspective on how we are solving today’s problems in medical RDT&E. Using a fact-based approach, we find realistic solutions that are practical, reasonable, and valuable to the user, yet still push the envelope. Most important, we create innovative AI-driven solutions our medical end-users can trust.
Our capabilities leverage over 20 years of AI development here at SoarTech and span from the training and operational domains. We are committed to creating solutions that are tailored to our users, provide realistic material, and reduce instructor workload. This includes augmenting a provider’s skillset to improve a patient’s experience and increase their survivability, for example, keeping good documentation.
Our solutions are designed to enable a provider to transcend their skills to provide optimal experiences in the continuum of patient care. Creating an environment for patients to get better care and providing a tool for instructors to be able to support that goal. Provided data is used to populate and analyze ERH, and provide recommendations to practitioners and patients.
We use many available technologies in combination with our proprietary capabilities and software to make inroads for better decision-making support tool for AR/VR, for example, Microsoft HoloLens, Pulse Physiology Model, DuJo, Physiology sensors, and Android Devices.