Artificial Intelligence

The realm of critical care medicine is always waiting for the game-changing innovation – that elusive breakthrough poised to dramatically transform practice and yield remarkable results. Various contenders have come and gone: surfactant therapy, synthetic colloids, drotrecogin alfa. While some have been consigned to the annals of history, a select few, such as low-tidal-volume ventilation, have endured. Others re-emerge time and again, hoping that they’ll have an evidence-based role somewhere. The level of excitement is not always correlated with the staying power of the innovation, and sometimes the hype can overshadow the reality.

For the past decade, we witnessed repeated attempts to integrate artificial intelligence techniques into clinical practice. Numerous discussions about the performance of image classification or predictive models have led to minimal real-world progress. Most falter, as their performance declines when they encounter data beyond their training and validation sets. Fatalist claims that these models would mean the end of one specialty or another have remained just that – claims.