The Future Arrived Yesterday

Matthew J. Kuhn, MD, FACR

Disclosures

Appl Radiol. 2019;48(4):30-31. 

In This Article

Introduction

The scientific literature typically describes transformational artificial intelligence (AI) tools in radiology with modifiers such as "impending" or "available soon." This makes it feel as if the true promise of AI is still waiting in the wings, anxiously waiting to come onstage.

It is true that, for most radiologists, what currently passes for AI is underwhelming and uninspiring compared to the futuristic visions of an "AI fellow" that can do most of our work for us (if not replace us entirely). Simplified and unremarkable algorithms—what I like to call "AI-lite—" have gained traction in many practices to help with a variety of important, but hardly revolutionary, functions: patient scheduling, editing of voice-activated dictations to ensure right- and left-sided correlation and gender agreement, and providing auto-text fill-ins for best practice follow-up recommendations.

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