Mediphany
Enhancing Radiology Workflows with AI-driven Solutions
The Challenge Summarized
Manually creating radiology reports has long been a time-consuming task, forcing radiologists to spend a disproportionate amount of time transcribing recordings and formatting reports instead of interpreting imaging results or attending to patients. This posed a critical challenge in the healthcare industry, calling for a solution that automated the transcription process while ensuring reports were accurate, customizable, and adaptable to various imaging types.
The Vision
With over 30 years of combined medical expertise, Mediphany’s team was on a mission to improve radiology reporting efficiency. Their goal was to deliver custom video explanations that provide clear, detailed insights into medical imaging results.
To achieve this goal, they needed to develop a solution that integrated speech-to-text technology with flexible templates.
The Scopic Solution
Scopic partnered with Mediphany to create an AI-driven solution that transforms speech from video recordings into detailed, structured reports. Our solution uses advanced AI models—such as OpenAI’s GPT-4 and Deepgram’s Nova-2-Medical model—to transcribe radiologists’ spoken input with high accuracy.
Additional key features include AI-driven template matching and customization, a color-coded review process, and advanced contextual learning.
This solution integrates seamlessly into Mediphany’s Recorder Desktop application, leveraging a robust AI pipeline built with technologies like Python, LangChain, and AWS Lambda for deployment.
Mediphany’s AI solution achieved over 85% accuracy in transcription and template mapping—improving productivity, streamlining workflows, and revolutionizing how radiologists create, manage, and analyze reports.
Speech-to-text transcription
A color-coded review process, contextual learning
Template matching and customization
Real-time report generation.
