The stream of data on Twitter provides a rich source of information that can help us understand trends and viewpoints in real-time.
One can easily harness Twitter data in an automated way and create large, structured datasets. The ability to do this feels intuitively powerful — what can we learn from the infinite patient/physician chatter? — and I spent quite some time pondering the highest yield use cases.
I concluded that a particularly meaningful application of Twitter data is understanding gender disparities in radiology and how they are changing with time. This makes sense because:
One of the coolest machine learning stories in recent memory involved the Google Duplex, a voice A.I. capable of calling a restaurant and making your dinner reservation while pretending to be human:
Simulating a personal assistant is cool, but it would be cooler to simulate a highly trained physician and potentially save lives. And given the massive hype surrounding artificial intelligence, I think it is fair to be ambitious.
“We wanted flying cars, instead we got 140 characters.”
— Peter Thiel
As a hybrid physician/engineer, I spend a lot of time pondering how new platforms can empower doctors.
I am particularly excited about the potential of smart speakers coupled with advances in A.I. and natural language processing (also looking at you, blockchain). I am bullish on conversational agents in general, previously building an iOS chatbot powered by Watson that simulates a human radiologist. Chatbots are cool and useful, but voice — that might be magic.
Sensing potential, I decided to hunker down with my trusty corgi, drink a bunch of coffee, and start building the cool voice tools I want to…
As a delightful weekend project, I sat down with my glorious corgi and lots of coffee and built a radiology assistant for Google Home. It is designed to assist healthcare providers with their radiology needs in a quick, conversational, hands-free way. Some video demonstrations:
Did you ever think we would have the technology to transform a modern bird into a prehistoric dinosaur? To, theoretically speaking, give a pig wings and make it fly? To evolve a mere cat into the far superior dog? Well, this is about to be you right now:
Enter CRISPR, hailed by Forbes as the “next step” in human evolution. …
You have a brilliant machine learning idea, hard-earned technical ability, and the capacity for airtight execution. Nonetheless, a challenge remains: navigating the complex layers of bureaucracy needed to please “the man” and attain permission to share your technology with the world.
Machine learning is clearly the hottest topic in HealthTech — you couldn’t use the restroom at RSNA 2017 without engaging in a discussion about whether A.I. beats radiologists at diagnosing pneumonia — yet most physicians have no understanding of the FDA approval process. …
There has been a lot of talk about Butterfly Network and their iQ ultrasound probe, which at first glance seems like just another point-of-care ultrasound probe in a saturated market. It certainly looks like the competition:
On closer examination, however, the iQ probe has features “under the hood” that make it considerably more powerful and interesting:
(A) It replaces the piezoelectric crystal with semiconductor chips.
Physician/engineer in Los Angeles, focused on using technology to improve healthcare. Corgi dad.