Digital Health

10 Apr 2019

14:10 — 14:30

Grace Hopper Stage

AI for Targeted Image Diagnostics - The Case for Narrow and Effective Business Cases

While the industry is certainly aiming in this direction, AI in healthcare will not be able to build an autonomous “Dr. AI” in the near-term. Still, this vision is causing anxiety and ethical questions amongst practitioners and patients alike. CellmatiQ embraces a strategy, in which we focus on development of AI-based automation for narrow and targeted tasks in the domain of medical image diagnostics. Combined with a data management strategy that relies on “gold-standard” training data, this allows to automate human tasks that are tedious, repetitive and/or error prone with immediate high benefit for doctors, while avoiding the perceived threat of being replaced. Equally, ethical questions are much easier to solve when focusing on steps of a workflow instead of an entire medical domain. We will present both, our data management platform and acquisition strategy, as well as the first products that provide such automation in diverse fields like orthodontics or ophthalmology.