Radiology Code Semantic Cleaner

Random Sample

Process random codes from the live dataset.

Upload Your Data

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Advanced Setup

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1 Choose Retriever Model

Select the embedding model for semantic search and candidate retrieval.

2 Choose Reranker Model

Select the AI model for reranking and scoring candidates.

3 Process Data

Choose your sample size:

Random Sample Size:

codes (1-1000)

Number of random codes to sample from the live dataset

Select Data Sources:

Choose which hospital systems to include in your sample

Select Modalities:

Choose which imaging modalities to include in your sample

Processing typically takes 30-60 seconds for 100 records

Cleaning Results

Original Codes

Clean Names

Consolidation Ratio

Modalities

Avg Confidence

Mappings

Prioritize unvalidated

	Original Code	Original Name	Clean Name	SNOMED FSN	Tags	Confidence	Actions

Radiology Code Semantic Cleaner

Random Sample

Upload Your Data

Advanced Setup

1 Choose Retriever Model

2 Choose Reranker Model

3 Process Data

Validation Pipeline

Review Mappings

Cleaning Results

Mappings

Validation Interface

Radiology Code Semantic Cleaner

Random Sample

Upload Your Data

Advanced Setup

1 Choose Retriever Model

2 Choose Reranker Model

3 Process Data

Validation Pipeline

Review Mappings

Cleaning Results

Mappings

Validation Interface

Configuration Editor

Top Consolidation Examples

Commit Validation Decisions

What happens next?

Validation Decisions Committed

What would you like to do next?

Continue Validating

New Processing Run

Start Over

Validation Commitment - User Information

Flag Mapping for Review