Artificial intelligence (“AI”) will likely drive many complex medical devices in the near future. But as with all things, AI can sometimes fail. Companies relying on AI to elevate their medical devices above the competition should be mindful of four common AI failure modes: AI functional errors, software rot, unexplained programming glitches, and the ever-present human factor.
Continue Reading 4 Common Ways That AI Driven Medical Devices Can Fail
Today, major healthcare companies are investing heavily into various AI-powered devices. For example, Zimmer Biomet and the New York City-based Hospital for Special Surgery recently inked a three-year deal to create the HSS/Zimmer Biomet Innovation Center for Artificial Intelligence in Robotic Joint Replacement. “The collaboration aims to develop decision support tools—powered by data collection and machine learning — to assist surgeons planning and predicting outcomes for robotic-assisted joint replacements.” Additionally, Johnson & Johnson have gone on record saying that they see “a huge opportunity to harness data, machine learning and artificial intelligence to help drive decision-making at all levels of healthcare.” As artificial intelligence starts playing a larger role in the modern healthcare space, a critical question will need to be answered: Are AI-powered solutions products or services?
Continue Reading Is Your Artificial Intelligence a Service or a Product?
During product development, it’s not unusual to discover certain failure points in a surgical robot’s design. For example, certain components, like nuts or bolts or screws, may become brittle when exposed to various substances or gasses commonly found in operating rooms. Similarly, prolonged use may cause cables and wires to become overstressed. Such component degradation may result in unwanted changes in the robot’s movement patterns or even complete structural failure. Issues like these, if not immediately addressed during product development, can become low-hanging fruit for plaintiffs’ lawyers.
Continue Reading Defeat Design Defect Claims Before They’re Filed
Until they become fully autonomous, surgical robots will only be as good as their human operators. Training for all surgeons, nurses, bedside assistants, and other surgical team members is critical to ensuring optimal patient outcomes. Thus, many manufacturers ask surgical staff to undergo instruction and demonstrations on how to set up, handle, and operate their systems. Such training can span several days and often includes simulations, scenario role-playing, and hands-on time with the robot. But what should a robot manufacturer do when asked by healthcare providers to modify its training curriculum and change certain important elements like course length, course content, or attendee roles and numbers?
Continue Reading Mitigating The Risks Of Training Curriculum Modification Requests