| title | TissueTech Ulcer RAG: Autonomous Bedside Telemetry & Clinical Intelligence Ecosystem |
|---|---|
| emoji | 🏥 |
| 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.
- 🧠 Vortex Clinical Assistant: Launch Space
- 📡 Bedside Telemetry Dashboard: Launch Space
- 🛠️ Muhammad Bilal: GitHub | LinkedIn
- 🔬 Mohamed Atef Elasalouty (Yumna / @dr_mohamed_atef_official): @yumna0010 | @dr_mohamed_atef_official | LinkedIn
- ⚡ Anthony Gaitanis (@anth0nygait7): @anth0nygait7 | LinkedIn
- 🩺 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)
- 🧠 Module 1: Vortex Clinical Assistant: 🚀 Launch Space — Deep Neon Cyber-Luxe Core Reasoning Bot.
- 📡 Module 2: Bedside Telemetry RAG Dashboard: 🚀 Launch Space — 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.
┌────────────────────────────────────────┐
│ Simulated Hardware Sensor Matrix │
│ (Pressure %, Temperature °C, Moist %)│
└───────────────────┬────────────────────┘
│
▼
┌────────────────────────────────────────┐
│ Automated Multi-Parameter Risk Index │
│ RI = (0.50*P) + (0.30*T) + (0.20*M) │
└───────────────────┬────────────────────┘
│
▼
┌────────────────────────────────────────┐
│ Semantic Context Engine (RAG Hub) │
│ (Maps Alert Zones to Research Context) │
└───────────────────┬────────────────────┘
│
▼
┌──────────────────────────┴──────────────────────────┐
▼ ▼
┌─────────────────────────────────────┐ ┌─────────────────────────────────────┐
│ 🧠 VORTEX CLINICAL ASSISTANT │ │ 📡 BEDSIDE TELEMETRY RAG NODE │
├─────────────────────────────────────┤ ├─────────────────────────────────────┤
│ • Task: Complex Clinical Reasoning │ │ • Task: Real-Time Sensor Processing │
│ • Target: Pathophysiology Modeling │ │ • Target: Tactical Nursing Alerts │
│ • Context: Background & Literature │ │ • Context: Hardware Array Layout │
└──────────────────┬──────────────────┘ └──────────────────▲──────────────────┘
│ │
└─────────────── [Context Handshake] ─────────┘
TissueTech-Ulcer-RAG/
├── README.md
├── vortex-clinical-assistant/
│ ├── app.py
│ └── requirements.txt
└── tissuetech-bedside/
├── app.py
└── requirements.txt