README.md

metadata

title: SentinelRx ADR Intelligence Prototype
emoji: 🧠
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 6.14.0
app_file: app.py
pinned: false

SentinelRx ADR Intelligence Prototype

This Hugging Face Space demonstrates the AI workflow layer for SentinelRx, a patient-facing adverse drug reaction detection companion.

What the prototype does

The Space lets a user select or paste a patient ADR testimony. It then shows:

1. Severity rating output
2. Medical information extraction output
3. Highlighted testimony evidence
4. Agentic triage recommendation
5. Structured ADR report preview

Important note

The severity model and medical information extraction model are currently placeholders.

Replace these functions in app.py when the final models are ready:

run_severity_model(text)
run_medical_extraction_model(text)

The rest of the prototype can stay the same.

Demo scenarios included

1. Severe reaction from patient testimony
2. Moderate ADR with uncertainty and missing information
3. Hidden safety risk in plain-language testimony

How to run locally

pip install -r requirements.txt
python app.py

Hugging Face Space setup

1. Create a new Hugging Face Space
2. Choose Gradio as the SDK
3. Upload:
   • app.py
   • requirements.txt
   • README.md
4. The Space should build automatically

Presentation framing

SentinelRx is a patient-facing ADR companion. The Hugging Face Space demonstrates the intelligence layer that would power the product: patient testimony goes in, severity and medical entities are extracted, then an agentic triage layer prioritizes the case and prepares an ADR report for human review.