Rad AI reduces real-time inference latency by 50% using Amazon SageMaker

This post is co-written with Ken Kao and Hasan Ali Demirci from Rad AI.

Rad AI has reshaped radiology reporting, developing solutions that streamline the most tedious and repetitive tasks, and saving radiologists’ time. Since 2018, using state-of-the-art proprietary and open source large language models (LLMs), our flagship product—Rad AI Impressions— has significantly reduced the time radiologists spend dictating reports, by generating Impression sections.

The Impression section serves as the conclusion of a radiology report, including summarization, follow-up recommendations, and highlights of significant findings. It stands as the primary result for the clinician who ordered the study, influencing the subsequent course of the patient’s treatment. Given its pivotal role, accuracy and clarity in this section are paramount. Traditionally, radiologists dictated every word of the impressions section, creating it from scratch for each report. This time-consuming process led to fatigue and burnout, and involved redundant manual dictation in many ...