Grounded Multimodal Retrieval-Augmented Drafting of Radiology Impressions Using Case-Based Similarity Search

1. 1Combine contrastive learning with multimodal embeddings to represent radiology cases
2. 2Implement case-based similarity search to retrieve relevant cases for drafting impressions
3. 3Use retrieval-augmented generation to draft impressions based on retrieved cases
4. 4Fine-tune the system using clinical data to improve accuracy and reliability

Radiologists and AI engineers on a team can benefit from this system as it provides more accurate and reliable drafting of radiology impressions, reducing the risk of hallucinations and improving clinical grounding.

💡 Multimodal retrieval-augmented generation can improve the accuracy and reliability of automated radiology report generation

📚 AI-generated radiology reports get a boost with multimodal retrieval-augmented generation #AIinRadiology