kristar0609/medgemma-lab-literacy-outputs

MedGemma Lab Results Literacy Companion Outputs

Educational content generated offline using google/medgemma-1.5-4b for the MedGemma Impact Challenge 2026.

Contents

• —generate-medgemma-content.py - Generation script using MedGemma 1.5 4B
• —medgemma-outputs.json - Generated educational content for 30 lab markers
• —Screenshots - Evidence of offline generation process

Model Tracing

Base Model: google/medgemma-1.5-4b (HAI-DEF) Generation Date: February 2026 Method: Local offline batch processing

What Was Generated

Structured educational content for 30 lab markers across 7 categories:

• —Blood Count (Hemoglobin, WBC, Platelets, etc.)
• —Metabolic Panel (Glucose, Creatinine, etc.)
• —Lipid Panel (HDL, LDL, Triglycerides, etc.)
• —Liver Function (ALT, AST, Bilirubin, etc.)
• —Thyroid (TSH, T4, etc.)
• —Vitamins/Minerals (Vitamin D, B12, Iron, etc.)

Each marker includes:

• —Plain-language explanation (what it measures, why doctors order it)
• —Population-level research context (biomedical literature patterns)
• —Food & nutrition patterns (USDA 2020 Dietary Guidelines)

Why Pre-Generation?

Instead of real-time API calls that would require uploading Protected Health Information, I embedded MedGemma's medical expertise directly into the application as static JSON.

This approach enables:

• —Complete privacy - no data transmission
• —Instant responses - no API latency
• —Offline capability - works without internet
• —Zero runtime costs - no inference fees
• —HIPAA-friendly - no PHI sent to servers

Usage in Application

The JSON is bundled in the web app and loaded by the Context Agent, enabling privacy-first lab literacy education.

Application: Lab Results Literacy Companion Live Demo: https://labcompanion.netlify.app Source Code: https://github.com/kriscodes09/LabCompanion-MedGemma-Challenge Demo Video: [] YouTube URL] Competition: MedGemma Impact Challenge (Kaggle, 2026)

License

CC BY 4.0 - Free to use with attribution