Has there been a turning-point moment when it felt like this technology moved from being more theoretical to something with real-world clinical applications?
Last spring, I saw a lecture by Peter Lee, who is president of Microsoft Research and a leader in developing AI-powered applications in medicine and scientific research, demonstrating how a large language model (LLM) could “understand” medical text and generate responses to questions. My jaw dropped.
We watched an LLM answer American Board of Internal Medicine questions with perfect explanations and rationale. He demonstrated how an audio recording of a clinic visit could be used to automatically generate a SOAP (subjective, objective assessment and plan) note. It was better than anything I would have drafted. He also showed how the LLM could directly ingest EHR data, without any modification, and provide a great diagnosis and treatment plan. Finally, LLM chatbots could carry on an interactive conversation with a patient that would be difficult to distinguish from a human physician.
The inevitability of AI-powered transformations in gastroenterology care became apparent.
Documentation, billing, and administrative work will be handled by AI. AI will collect and organize information for me. Chart reviews and even telephone/email checkups on patients will be a thing of the past. AI chatbots will be able to discuss an individual patient’s condition and test results. Our GI-AI assistants will proactively collect information from patients after hospitalization or react to a change in labs.
AI will soon be an amazing diagnostician and will know more than me. So do we need to polish our resumes for new careers? No, but we will need to adapt to changes, which I believe on the whole will be better for gastroenterologists and patients.
What does adaptation look like for gastroenterologists over the next handful of years?
Like any other tool, gastroenterologists will be figuring out how to use AI prediction models, chatbots, and imaging analytics. Value, ease of use, and information-gain will drive which AI tools are ultimately adopted.
Memory, information recall, calculations, and repetitive tasks where gastroenterologists occasionally error or find tiresome will become the job of machines. We will still be the magicians, now aided by machines, applying our human strengths of contextual awareness, judgment, and creativity to find customized solutions for more patients.
That, I think, is the future that we are reliably moving toward over the next decade — a human-computer cooperative throughout gastroenterology (including IBD) and, frankly, all of medicine.
A version of this article appeared on Medscape.com.
