albertzhzhou-droid

albertzhzhou-droid / ParkinSUM

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Local-first Flutter prototype for Parkinson's disease diet-medication education and levodopa-food interaction awareness.

clinical-decision-support dart diet-tracking digital-health flutter
19
2
85% credibility
Found May 31, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Dart
AI Summary

ParkinSUM Companion is a local-first Flutter app designed to help people learn about potential interactions between food and Parkinson's disease medications. Users can log meals from a food catalog, add their medications, and receive educational warnings when the app detects potential food-drug interactions. Every warning comes with evidence-based explanations and source references. The app explicitly states it is for educational awareness only and is not a medical device, diagnosis tool, or substitute for professional healthcare advice. It uses deterministic rules (not AI) and keeps data on the user's device by default.

How It Works

1
🔍 You discover the app

You hear about a tool that helps people with Parkinson's understand how their diet might affect their medication, and you want to learn more.

2
📱 You install and open the app

The app welcomes you and asks a few simple questions about where you live and what matters to you for your health education.

3
🍽️ You log your meals

You browse a searchable food catalog and add what you ate today, like oatmeal for breakfast or chicken for lunch.

4
💊 You add your medications

You select your Parkinson's medications from an official drug catalog, entering what you take and when you take it.

5
The app checks for interactions
✅
No concerns found

The app shows a green summary saying everything looks fine for this meal and medication combination.

⚠️
Something to note

The app shows a warning with a clear explanation of why it flagged something, plus where the information comes from.

6
📖 You read the explanation

Every warning includes plain-language explanations and references to official sources, so you understand exactly why something was flagged.

🎓 You feel more informed

You now have educational awareness about food-medication patterns for Parkinson's, with clear disclaimers that this is learning, not medical advice.

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AI-Generated Review

What is ParkinSUM?

ParkinSUM is a local-first Flutter app that helps people learn about how food interacts with Parkinson's medications, specifically levodopa. Users log meals and medications, and the app runs deterministic rules to flag potential interactions like high-protein meals reducing levodopa absorption. Every flag includes an evidence-linked explanation citing official drug labels and clinical literature. The app works entirely offline by default, with optional Firebase hooks for internal validation only.

Why is it gaining traction?

This stands out because it treats safety as a first-class architectural concern. Every rule that fires carries structured provenance: source references, jurisdiction metadata, input fields used, and explicit "not medical advice" boundaries. The mechanistic conflict engine models gastric emptying and amino-acid competition with literature-informed parameters, but never fabricates missing data. Developers reviewing this get a production-grade example of how to build evidence-linked, auditable decision systems without relying on black-box AI.

Who should use this?

Flutter developers building health education apps will find the architecture worth studying. Digital health researchers can use the deterministic replay scenarios to demonstrate how evidence-linked rules behave across different meal and medication combinations. Academic teams evaluating local-first patterns for sensitive data will appreciate the Firebase boundary design. This is explicitly not for patient care or clinical decision-making.

Verdict

With a 0.85% credibility score and only 19 stars, this is a prototype showcase, not production-ready software. The documentation is extensive and the safety guardrails are thoughtful, but test coverage and community traction remain minimal. Worth exploring for architecture inspiration if your use case matches the educational awareness model.

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