Medical Assistant for Radiologists AI-Enhanced Diagnostic Support System with RAG + BioGPT

Result

Client Overview

▫️Client: Confidential (network of 14 imaging centers)
▫️Industry: Healthcare / Medical Imaging Engagement
▫️Duration: 20 weeks (including FDA clearance process)
▫️Team Deployed: 2 AI specialists, 1 medical NLP expert, 1 healthcare compliance officer from TechSteck Solutions

Objectives

- ▫️Create a HIPAA-compliant assistant that analyzes historical patient reports
- ▫️Integrate medical literature and up-to-date research evidence
- ▫️Generate preliminary report drafts based on imaging findings
- ▫️Support differential diagnosis with evidence-based suggestions
- ▫️Maintain strict regulatory compliance with audit trails

Solution

TechSteck Solutions developed a comprehensive medical RAG system using:

- - - - ▫️BioGPT for medical-specific reasoning and generation
      - ▫️Haystack framework for retrieval pipelines
      - ▫️PubMed/PMC datasets for medical knowledge base
      - ▫️Azure HIPAA-compliant infrastructure
      - ▫️Custom radiology-specific embedding models

Workflow Architecture

Lessons Learned

- - - ▫️Domain-specific embeddings crucial for medical accuracy
    - ▫️Chunking strategies needed special adaptation for medical reports
    - ▫️Radiologist feedback loop improved system performance by 31%
    - ▫️BioGPT outperformed general LLMs by significant margin for medical content
    - ▫️Regular retraining with new literature essential for keeping recommendations current

Conclusion

- - - By combining RAG capabilities with specialized medical AI, TechSteck Solutions transformed the client’s diagnostic workflow—enhancing accuracy, efficiency, and evidence-based practice while maintaining full regulatory compliance and improving patient outcomes.

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