The road to clinical implementation
With further research and validation, deep learning models for gastroenterology are likely to play a role in clinical decision-making, according to Dr. Shung. But to reach the clinic floor, developers will need to outsmart some more fundamental obstacles. “The main thing that’s really barring [AI risk modeling] from being used is the reimbursement issue,” he said, referring to uncertainty in how payers will cover associated costs.
Dr. Sushovan Guha
In an interview, Sushovan Guha, MD, PhD, moderator of the virtual session and codirector of the center for interventional gastroenterology at UTHealth (iGUT) in Houston, pointed out another financial unknown: liability.
“What happens if there is an error?” he asked. “It’s done by the computers, but who is at fault?”
In addition to these challenges, some clinicians may need to be persuaded before they are willing to trust an algorithm with a patient’s life.
“We have to have community physicians convinced about the importance of using these tools to further improve their clinical practice,” Dr. Guha said. To this end, he added, “It’s time for us to accept and adapt, and make our decision-making process much more efficient.”
The investigators disclosed no relevant conflicts of interest.