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AI in Radiology Reporting

A Mediphany Case Study

See how Scopic helped Mediphany automate radiology reports using AI speech-to-text, improving accuracy and saving radiologists from hours of paperwork each week. 

The Results at a Glance

AI in Healthcare Innovation

85%

Transcription Accuracy in Speech-to-Text conversion

85%

Mapping Accuracy achieved with fixed examples and robust scoring

Significant time savings

addressing the industry-average 11 hours of administrative work 

Streamlined workflow integration

through a unified dashboard

The Results at a Glance

AI in Healthcare Innovation

With over 30 years of combined medical expertise, Mediphany simplifies complex medical imaging results for patients and professionals alike. Their innovative approach combines cutting-edge tools like 3D imaging models, real-time video explanations, and comparative analyses to provide patients and practitioners with precise, actionable insights.
The challenge was clear: with an industry average of radiologists spending 11 hours per week on administrative tasks, particularly in report creation. This administrative burden created three critical pain points:

Time-Intensive Reporting

Time-Intensive Reporting

Radiologists spent up to 25% of their hours creating detailed reports, reducing their time for diagnoses and treatment.

Template Inflexibility

Template Inflexibility

Traditional report templates didn’t adapt well to various medical imaging types (e.g., MRI, CT), often resulting in inefficiencies and mismatches. 

Accuracy and Flexibility

Accuracy and Flexibility

A solution was needed that could deliver precise, structured transcriptions while remaining adaptable to different use cases. 

Mediphany needed a seamless, AI-driven radiology software that could generate structured reports in real-time, ensure accuracy, and scale across diverse use cases. 

The Solution

AI Report Automation 

Scopic partnered with Mediphany to create a powerful AI Speech-to-Text (STT) solution that automates radiology report generation. This innovative system combined with Large Language Models (LLMs), transformed spoken words into structured, accurate, and real-time reports. 

Here’s how it works: 

Speech-to-Text Conversion 

Leveraging AI technologies like OpenAI GPT-4 and Deepgram’s Nova-2-Medical model, the system transcribes practitioners’ spoken input into written text with high accuracy. 

Template Matching 

Leveraging AI technologies like OpenAI GPT-4 and Deepgram’s Nova-2-Medical model, the system transcribes practitioners’ spoken input into written text with high accuracy. 

Color-Coded Text Identification

Leveraging AI technologies like OpenAI GPT-4 and Deepgram’s Nova-2-Medical model, the system transcribes practitioners’ spoken input into written text with high accuracy. 

Continuous Learning 

Leveraging AI technologies like OpenAI GPT-4 and Deepgram’s Nova-2-Medical model, the system transcribes practitioners’ spoken input into written text with high accuracy. 

Seamless Integration

Leveraging AI technologies like OpenAI GPT-4 and Deepgram’s Nova-2-Medical model, the system transcribes practitioners’ spoken input into written text with high accuracy. 

Technology Stack

The system leverages recent advances in AI in healthcare, including:

Speech
Recognition

Deepgram’s Nova-2-Medical model. 

AI & Natural Language Processing

OpenAI API with LangChain for data mapping and contextual understanding. 

Deployment

Python backend running on AWS Lambda for scalability and real-time performance. 

Continuous Learning

Chroma’s vector store allows the system to access prior reports, enabling similarity searches and ongoing improvements.

Why It Worked

AI in Healthcare Success Factors

The solution’s success can be attributed to three key factors

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Seamless Integration
Built directly into Mediphany's Recorder Desktop application
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Advanced AI Technology
Combination of leading AI models and healthcare-specific training 
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Continuous Learning Capabilities
Vector store implementation for ongoing improvement

A Workflow Transformed

Before and After AI Integration

Before

Hours spent on manual
transcription

Errors and mismatched
templates

High stress and less time for actual radiologist work

After

Reports generated in real-time with 85%+ accuracy

Dynamic templates ensure precise, structured outputs. 

Radiologists spend more time diagnosing and treating patients 

Now It’s Your Turn:

Implement AI in Healthcare Practice

Discover how Scopic can revolutionize your business with tailored,
AI solutions for healthcare and other industries.
 Schedule a free consultation to explore what’s possible. 

Bonus

Explore the Impact of AI in Radiology 

Want to learn more about the trends shaping the future of radiology? Read our blog for insights on AI’s pros, cons, and transformative potential in the field. 

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