Harnessing artificial intelligence in gastroenterology and hepatology: Current applications and future perspectives

Figure 1 Generic hype cycle applied to artificial intelligence methodologies. Artificial intelligence innovations typically follow a trajectory from the innovation trigger and peak of inflated expectations, through the trough of disillusionment, slope of enlightenment, and eventually reach the plateau of productivity. Each methodology (e.g., supervised learning, unsupervised learning, reinforcement learning, foundation models) traverses this pathway at its own pace, influenced by data availability, regulatory maturity, interpretability, and clinical need.