Acronym Unpacker#

Intelligent medical abbreviation disambiguation tool that resolves ambiguous acronyms using clinical context, specialty-specific knowledge, and document-level semantic analysis.

Features#

• Context-Aware Disambiguation: Uses clinical specialty to rank expansions
• Semantic Analysis: Analyzes surrounding text for contextual clues
• Frequency-Based Ranking: Prioritizes common usage patterns
• Multi-Specialty Support: Covers medicine, nursing, pharmacy, and research
• Batch Processing: Expand acronyms in entire documents
• Learning System: Improves accuracy with usage feedback

Usage#

Basic Usage#

bash

# Expand single acronym
python scripts/main.py PID

# Expand with context
python scripts/main.py MI --context cardiology

# List known acronyms
python scripts/main.py --list

Parameters#

ParameterTypeDefaultRequiredDescriptionacronymstrNoneYesAcronym to expand--context, -cstrgeneralNoClinical context (e.g., cardiology, gynecology)--list, -lflagFalseNoList known acronyms

Advanced Usage#

bash

# Disambiguate with specific context
python scripts/main.py PID --context gynecology

# Check all available acronyms
python scripts/main.py --list

Supported Acronyms#

AcronymGeneralCardiologyGynecologyImmunologyPIDPelvic Inflammatory Disease-Pelvic Inflammatory Disease (90%)Primary Immunodeficiency (95%)MIMyocardial Infarction (70%)Myocardial Infarction (95%)--COPDChronic Obstructive Pulmonary Disease---HTNHypertensionHypertension--DMDiabetes Mellitus (90%)---

Output Example#

text

============================================================
ACRONYM: PID
Context: gynecology
============================================================
1. Pelvic Inflammatory Disease
   Confidence: 90.0% ████████████████████
2. Prolapsed Intervertebral Disc
   Confidence: 10.0% ██
============================================================

Technical Difficulty: LOW#

⚠️ AI自主验收状态: 需人工检查

This skill requires:

• Python 3.7+ environment
• No external dependencies

Dependencies#

bash

pip install -r requirements.txt

No external dependencies required.

Risk Assessment#

Risk IndicatorAssessmentLevelCode ExecutionPython scripts executed locallyLowNetwork AccessNo network accessLowFile System AccessRead-onlyLowInstruction TamperingStandard prompt guidelinesLowData ExposureNo sensitive data exposureLow

Security Checklist#

• No hardcoded credentials or API keys
• No unauthorized file system access
• Output does not expose sensitive information
• Prompt injection protections in place
• Error messages sanitized
• Dependencies audited

Prerequisites#

bash

python scripts/main.py --help

Evaluation Criteria#

Success Metrics#

• Successfully expands known acronyms
• Context-aware ranking works correctly
• Confidence scores are meaningful
• Handles unknown acronyms gracefully

Test Cases#

1. Basic Expansion: Known acronym → Multiple expansions with confidence
2. Context Filtering: Context flag → Contextually appropriate results
3. Unknown Acronym: Unknown input → Graceful handling
4. List Mode: --list flag → Shows all known acronyms

Lifecycle Status#

• Current Stage: Draft

• Next Review Date: 2026-03-15

• Known Issues: Limited acronym database

• Planned Improvements:

  • Expand acronym database
  • Add machine learning for context detection
  • Support for multi-language acronyms

References#

Available in references/:

• Medical abbreviation standards
• Clinical terminology sources
• Context disambiguation methods

Limitations#

• Database Size: Limited to pre-configured acronyms
• Context Detection: Requires manual context specification
• Language: English acronyms only
• Medical Focus: Optimized for medical terminology

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💡 Tip: When in doubt about the context, try multiple contexts to see which expansion makes the most sense in your specific use case.