badoni-sowmya/Anemi-AI
Domaine:
healthcareType de record:
software
Créateur:
bad
Hôte:
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> **Non-invasive anaemia screening and haemoglobin prediction using computer vision and deep learning.**
AnemiAI eliminates the need for blood draws in preliminary anaemia screening by analyzing RGB color features extracted from lower eyelid images — making clinical-grade screening accessible in low-resource environments where laboratory infrastructure is unavailable.
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## The Problem
Over 1.6 billion people globally are affected by anaemia. Diagnosis traditionally requires invasive blood collection and laboratory equipment — creating a significant gap in access for rural, remote, and resource-constrained communities. AnemiAI bridges this gap with a camera, a machine learning model, and a web browser.
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## How It Works
1. User captures an image of their lower eyelid via the web interface
2. The system extracts normalized RGB pixel intensity features from the palpebral conjunctiva
3. A dual-output feedforward neural network runs inference:
- **Classifier** → Anaemic / Non-Anaemic
- **Regressor** → Estimated haemoglobin (Hb) level in g/dL
4. Results are returned in real time via a REST API
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## Architecture
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## Tech Stack
| Layer | Technology |
|---|---|
| Frontend | React.js, Webcam API |
| Backend | Python, Flask |
| ML Framework | TensorFlow / Keras |
| Data Processing | NumPy, Scikit-learn |
| Database | MongoDB |
---
## API Reference
### `POST /predict`
Accepts normalized RGB percentages extracted from the eyelid region and returns anaemia classification and predicted haemoglobin level.
**Request**
```json
{
"red": 45.2,
"green": 29.1,
"blue": 25.7
}
```
**Response**
```json
{
"anaemia": "Yes",
"hb": 9.8 …