| title | TissueTech Ulcer RAG: Autonomous Bedside Telemetry & Clinical Intelligence Ecosystem |
|---|---|
| emoji | π₯ |
| colorFrom | cyan |
| colorTo | purple |
| sdk | gradio |
| pinned | true |
| license | mit |
| short_description | Real-time clinical telemetry analysis ecosystem utilizing Llama 3.3 and Groq Cloud LPU framework. |
"Synthesizing Biomedical Telemetry, Synchronizing Multi-Parameter Risk Indexing, Automating Bedside Patient Care."
TissueTech Ulcer RAG is an enterprise-grade, highly decoupled Clinical Decision Support System (CDSS) built during the 72-Hour Research Hackathon. Designed for high-density healthcare environments, this cognitive ecosystem coordinates advanced LLMs via Groq LPU acceleration and local semantic knowledge retrieval (RAG) to process real-time multi-modal streaming data from an affordable hospital mattress matrix.
- π§ Vortex Clinical Assistant: Launch Space
- π‘ Bedside Telemetry Dashboard: Launch Space
- π οΈ Muhammad Bilal: GitHub | LinkedIn
- π¬ Mohamed Atef Elasalouty (Yumna / @dr_mohamed_atef_official): @yumna0010 | @dr_mohamed_atef_official | LinkedIn
- β‘ Anthony Gaitanis (@anth0nygait7): @anth0nygait7 | LinkedIn
- π©Ί Zaheen: LinkedIn
The system implements a strict automated data mapping pipeline:
- Input: Raw telemetry (Pressure, Temperature, Moisture).
-
Process: Multi-parameter Risk Index calculation (
$RI$ ). - Output: Context-injected AI medical reports via RAG.
The complete clinical intelligence network is deployed across two specialized, synchronized software environments hosted live on Hugging Face Spaces: (Muhammad Bilal)
- π§ Module 1: Vortex Clinical Assistant: π Launch Space β Deep Neon Cyber-Luxe Core Reasoning Bot.
- π‘ Module 2: Bedside Telemetry RAG Dashboard: π Launch Space β Real-Time Hardware Emulation Matrix.
Unlike generic, consumer-grade large language wrappers constrained by static training data, this system implements a strict automated data mapping pipeline. The local inference loop intercepts incoming raw telemetry, structures it, and matches it with peer-reviewed biomedical texts.
ββββββββββββββββββββββββββββββββββββββββββ
β Simulated Hardware Sensor Matrix β
β (Pressure %, Temperature Β°C, Moist %)β
βββββββββββββββββββββ¬βββββββββββββββββββββ
β
βΌ
ββββββββββββββββββββββββββββββββββββββββββ
β Automated Multi-Parameter Risk Index β
β RI = (0.50*P) + (0.30*T) + (0.20*M) β
βββββββββββββββββββββ¬βββββββββββββββββββββ
β
βΌ
ββββββββββββββββββββββββββββββββββββββββββ
β Semantic Context Engine (RAG Hub) β
β (Maps Alert Zones to Research Context) β
βββββββββββββββββββββ¬βββββββββββββββββββββ
β
βΌ
ββββββββββββββββββββββββββββ΄βββββββββββββββββββββββββββ
βΌ βΌ
βββββββββββββββββββββββββββββββββββββββ βββββββββββββββββββββββββββββββββββββββ
β π§ VORTEX CLINICAL ASSISTANT β β π‘ BEDSIDE TELEMETRY RAG NODE β
βββββββββββββββββββββββββββββββββββββββ€ βββββββββββββββββββββββββββββββββββββββ€
β β’ Task: Complex Clinical Reasoning β β β’ Task: Real-Time Sensor Processing β
β β’ Target: Pathophysiology Modeling β β β’ Target: Tactical Nursing Alerts β
β β’ Context: Background & Literature β β β’ Context: Hardware Array Layout β
ββββββββββββββββββββ¬βββββββββββββββββββ ββββββββββββββββββββ²γγγγβββββββββββββββββββ
β β
ββββββββββββββββ [Context Handshake] ββββββββββ
TissueTech-Ulcer-RAG/
βββ README.md
βββ vortex-clinical-assistant/
β βββ app.py
β βββ requirements.txt
βββ tissuetech-bedside/
βββ app.py
βββ requirements.txt