*The themes in this blog originated from the IRIA- ICRI webinar on the same topic that happened on May 14 2020. The presenters in the webinar were Prashant Warier (Founder & CEO, Qure.ai), Angel Alberich-Bayarri (Founder & CEO, QUIBIM), Vijayananda J (Fellow — AI, Philips Healthcare). The session was moderated by Vidur Mahajan (Head of R&D, Centre for Advanced Research in Imaging, Neurosciences & Genomics (CARING)
The adoption of AI in Radiology will be influenced by the radiologists to a large extent. Radiology managers and hospital administrators can bring up new solutions to enhance or impact the radiology workflow. But if radiologists don’t validate them and approve them, the algorithms are not getting anywhere. We have been made to believe so far that this is the only contribution that radiologists can offer in the whole AI boom, projected by many top computer scientists & tech evangelists as an existential threat to us.
After hearing three established people from the other side (of clinical radiology) talk for over an hour on what they expect from radiologists, I was pleasantly surprised.
I got three main insights from this conversation.
Open-mindedness is a virtue of Intellectuals, and best radiologists too
All panelists agreed that having an open-mind to continuous learning & adoption of emerging roles is the essential quality that they are looking for in radiologists willing to work with them or for them. As Prashant expressed this very nicely “a Radiologist with the ability to think beyond what is possible today will be desirable for all tech companies”. I can’t agree more as these challenging times have only re-iterated this concept that we may have to learn to adapt to fast-changing practices and radiologists have always been good at that. Some of the best MR experts in the world today had never seen MR images during their training!
They still want us to do annotations, only better than before
Despite fast-paced improvements in the architectures of the AI algorithms, their dependency on clean curated data is not going away. Every developer will dream of data with the best annotations. This webinar re-iterated this. As Vijayananda put it across succinctly “ Radiologists should learn to use tool-boxes & tool kits to do faster and better annotations”. I have a personal experience of annotating over 6,000 X-rays for pneumothorax continuously for over a month. I can say this with certainty, we can’t love it. But it can be one of the best places to start and get a peek into what goes inside these algorithms. Behind all glamour & good AI, is some radiologist\’s hard work!
They don’t want us to build products but manage them & spread the word around
It is both a relief and disappointment to learn that none of the panelists expect us to code or develop algorithms. Coding for algorithms is like playing a sport for a career. You can be good at playing a sport in your gully or among peers but that can’t get you selected for a national team. It is unfair to expect startups or even established tech companies to bet their money on a hobbyist developer. So I regret to break this to all radiologists dreaming to create your algorithm. You won’t be needed for that.
But they all want us to understand the basic concepts behind the algorithm development and the statistical principles behind the validation of these algorithms. The most surprising insight for me personally was all four (including the moderator, Vidur) want to get radiologists on the business development side. As Angel clarified “We don’t want radiologists for sales (if you say that, radiologists will run away). Traditional sales won’t work for AI solutions, but we want radiologists to be part of scientific marketing”.
To summarize from across the board: “The most wanted radiologist for tech companies is the one who can participate in the ideation of a product, help build it, differentiate between different products, quantify the difference and spread the word to the world”.
It seems the tech firms have many interesting roles to offer for us, are we ready for those roles? Or Is this too much to ask for?
https://medium.com/@vasanthdrv/what-do-ai-tech-companies-want-from-radiologists-ae95c373872
