I am a pediatric cardiologist and have cared for children with heart disease for the past three decades. In addition, I have an educational background in business and finance as well as healthcare administration and global health – I gained a Masters Degree in Public Health from UCLA and taught Global Health there after I completed the program.
“Anything that could give rise to smarter-than-human intelligence—in the form of Artificial Intelligence, brain-computer interfaces, or neuroscience-based human intelligence enhancement – wins hands down beyond contest as doing the most to change the world. Nothing else is even in the same league.”
Eliezer Yudkowsky, American AI theorist
I had the privilege of giving a keynote talk on the utility and applicability of artificial intelligence in the realm of medical devices at the 10X Medical Device Conference this past week (invited by my good friend Joe Hage), and here is a summary of some of my thoughts about how these two realms can be interrelated in the near future in the form of three takeaways:
- Real-time AI in medical devices to generate and analyze data. The MIT researchers have devised “tinyML”, a neural net that can be embedded into a microprocessor to analyze data. This futuristic capability of devices with edge “AI” will transform the internet of things into the internet of everything. This is equivalent to the formation of a peripheral nervous system for real-time analytics organized into a central nervous system.
- Real world. Real world data for medical devices assessment of effectiveness. The 2022 Nobel Prize winners in Economics and Physics have been given to investigators who have studied complex data in the real world (“real world data”). The future of clinical research with medical devices will be more on real world data and less on registry data so that real world complexities can be studied by researchers.
- Real impact. Federated learning for a device-specific learning system. The individuals with medical devices and sensors currently generate data that do not communicate with one another. A future learning system via federated learning that incorporates all the disparate medical devices, even different types, can become a clinical learning system. The multimodal AI strategy can allow sharing of insights without sharing raw data in the future.
In addition to the future of clinical AI of medical devices, many other topics will be discussed at our next AIMed Global Summit 2023 scheduled for May of 2023 at the Anaheim Convention Center. See you then! Book your place at AIMed 2023 now.
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