There are two key challenges in medical procedures training:
1. Access to medical experts for feedback
2. Access to patients under various pathologies.
Fortunately, #2 is beginning to be solved through advances in medical simulators, from diverse manikins (e.g. motorized soft tissue manikins that can simulate different stages of a heart attack) to virtual reality experiences.
On the contrary, problem #1 remains virtually untouched. Expert time remains valuable, which means they can’t provided 1:1 time to individual learners. Expert attendants and nurses are also not geographically scalable. Finally, studies show that students tend to learn better [1] when they are provided a certain degree of independence, with the right guidance.
Our RetroActivity platform is able to track the status of a complex medical procedure from just a handful of expert demonstrations for assessment, and we are working with NASA Exploratory Medical Capability team (ExMC) and CAE Healthcare to commercialize this capability. This capability enables building computational models of expert performance of medical tasks, and comparing learner performances against these benchmarks.
[1] Comparison of learning outcomes for teaching focused cardiac ultrasound to physicians: A supervised human model course versus an eLearning guided self- directed simulator course. Canty et al. Journal of Critical Care 49 (2019) 38-44.
Huy takes our product roadmap and figures out what’s achievable with today’s AI advances, and what we need to invent to solve our customers’ pain points.
Huy led teams of scientists and engineers at NEC and invented technologies for driver assistance systems that are part of 500,000+ Honda cars. He is an inventor on more than 20 US patents, and his research papers are cited by every lab from MIT, Stanford, and CMU to Apple, Google, and Baidu.
Michael works closely with our marquis customers to understand their needs, and figures out the best solution that immediately adds dollars to their bottom line.
Michael has almost 20 years of enterprise sales experience. He has held sales leadership roles at pioneering AI and computer vision startups.
Andrey takes inventions and converts them into innovations. He leads our product engineering team to turn our scientific prototypes into robust customer-facing products.
Andrey co-founded and successfully exited a startup to immigrate to the US. He spent his next eight years building the core data science infrastructure for Amazon’s supply chain planning team, and the CV/ML infrastructure for Microsoft’s HoloLens organization.
Zeeshan focuses on delighting our customers by understanding their needs and defining product and strategy to meet and exceed these needs. He works closely with our sales leadership to grow our customer base.
Zeeshan was a scientific leader at Microsoft’s HoloLens division, where he invented AI technologies to assist frontline workers across industries. Earlier, he shipped IoT platforms and visual defect detection software for manufacturers at Siemens and MVTec GmbH.
