Rad AI Adds Speech Recognition to Rad AI Reporting

Rad AI, a provider of radiology workflow solutions, has added speech recognition technology to Rad AI Reporting for dictation in radiology.

The new system doesn't just transcribe words; it understands clinical context, recognizes uniqueness and adapts to how each radiologist works.

"The foundation of great radiology care is a fast, accurate report," said Doktor Gurson, CEO of Rad AI, in a statement. "Today, radiologists are limited by reporting tools that simply transcribe words but don't understand the user behind them, still missing subtleties, struggling with clinical terminology, and forcing radiologists to spend valuable time correcting basic errors. We built this technology to understand context so that radiologists can return focus to diagnosis, not documentation."

Rad AI's new multi-model architecture combines multiple speech engines powered by Rad AI's modeling and unique "voting" algorithm that determines the most accurate understanding in real time.This approach ensures consistent, high-fidelity results across all reading environments, from quiet reading rooms to challenging acoustic conditions, such as emergency department workstations. Fine-tuned language models handle radiology-specific terminology, measurements, modifier,s and even context-based interpretation cues such as laterality and sequence timing.

By integrating workflow analytics, Rad AI's reporting engine goes beyond speech recognition, where radiologists spend unnecessary time dictating redundant information, such as "pertinent negatives" or repeated phrases already captured in templates.

Other key advancements include the following:

• Multi-model precision with an algorithm that dynamically compares multiple transcriptions simultaneously to select the most accurate output.
• Adaptive accuracy with custom language models fine-tuned for radiology vocabulary and syntax.
• Workflow intelligence with real-time analytics, highlighting opportunities to shorten dictation and streamline templates.
• Seamless integration within the existing Rad AI Reporting interface.

"Every innovation we build starts from the same question: what slows radiologists down?" added Gurson. "From AI-driven impression generation to now speech intelligence, we're removing friction from the reporting process so radiologists can spend more time on what matters most – their patients."