Spaces:
Running
Running
File size: 1,163 Bytes
01070c9 cd846d7 01070c9 c29becc 01070c9 cd846d7 01070c9 cd846d7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | ---
title: HeartWatchAI
emoji: ❤️
colorFrom: red
colorTo: pink
sdk: gradio
sdk_version: 5.6.0
app_file: app.py
pinned: false
short_description: AI-powered 12-Lead ECG Analysis
hf_oauth: false
---
# HeartWatch AI
AI-powered 12-Lead ECG analysis using deep learning models.
## Features
- **77-Class ECG Diagnosis**: Detect 77 different cardiac conditions
- **LVEF Prediction**: Predict left ventricular ejection fraction < 40% and < 50%
- **AFib Risk**: 5-year atrial fibrillation risk prediction
- **Interactive Visualization**: Clinical 4x3 lead layout with ECG paper grid
## Models
This demo uses EfficientNetV2 models from the DeepECG project:
- `heartwise/EfficientNetV2_77_Classes`
- `heartwise/EfficientNetV2_LVEF_40`
- `heartwise/EfficientNetV2_LVEF_50`
- `heartwise/EfficientNetV2_AFIB_5y`
## Input Format
- NumPy array (.npy file)
- Shape: (2500, 12) or (12, 2500)
- 12 standard leads: I, II, III, aVR, aVL, aVF, V1-V6
- 10 seconds at 250 Hz sampling rate
## Disclaimer
This is a research demonstration tool. Predictions should NOT be used for clinical decision-making. Always consult qualified healthcare professionals for medical advice.
|