| name | ehr-semantic-compressor |
| description | AI-powered EHR summarization using Transformer architecture to extract key clinical information from lengthy medical records |
| version | 1.0.0 |
| category | Clinical |
| tags | [] |
| author | AIPOCH |
| license | MIT |
| status | Draft |
| risk_level | Medium |
| skill_type | Tool/Script |
| owner | AIPOCH |
| reviewer | |
| last_updated | 2026-02-06 |
EHR Semantic Compressor
Overview
AI-powered EHR summarization using Transformer architecture to extract key clinical information from lengthy medical records. This skill processes lengthy Electronic Health Record (EHR) documents and generates structured, clinically accurate summaries.
Technical Difficulty: High
When to Use
- Input contains lengthy EHR documents (1600+ words) requiring summarization
- Clinical records need structured extraction of key information
- Quick review of patient history, medications, allergies, or diagnoses is needed
- Medical documentation requires compression while maintaining accuracy
Core Features
- Fast Processing: Process lengthy EHR documents (1600+ words) in 10-20 seconds
- Structured Summaries: Generate bullet-point summaries (200-300 words)
- Critical Information Extraction:
- Patient allergies and adverse reactions
- Family medical history
- Current and past medications
- Diagnoses and conditions
- Vital signs and lab results
- Procedures and surgeries
- Clinical Accuracy: Maintains completeness of medical information
Usage
Basic Usage
python scripts/main.py --input ehr_document.txt --output summary.json
Input Format
{
"ehr_text": "Full EHR document text...",
"max_length": 300,
"extract_sections": ["allergies", "medications", "diagnoses", "family_history"]
}
Output Format
...
...
...
...
