https://github.com/bhimrazy/otitis-media-detection-using-deep-transfer-learning
Otitis Media Detection using Transfer Learning is a deep learning technique that uses pre-trained models to quickly and accurately diagnose middle ear infections.
https://github.com/bhimrazy/otitis-media-detection-using-deep-transfer-learning
ear-disease-prediction fastapi healthcare-application nextjs pytorch tailwindcss
Last synced: 3 months ago
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Otitis Media Detection using Transfer Learning is a deep learning technique that uses pre-trained models to quickly and accurately diagnose middle ear infections.
- Host: GitHub
- URL: https://github.com/bhimrazy/otitis-media-detection-using-deep-transfer-learning
- Owner: bhimrazy
- License: mit
- Created: 2022-07-31T12:07:25.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2024-03-09T15:04:12.000Z (over 2 years ago)
- Last Synced: 2025-01-17T11:13:39.492Z (over 1 year ago)
- Topics: ear-disease-prediction, fastapi, healthcare-application, nextjs, pytorch, tailwindcss
- Language: Jupyter Notebook
- Homepage: https://otitis-media-detection.vercel.app
- Size: 70.5 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Otitis Media Detection Using Transfer Learning
Otitis Media Detection using Transfer Learning is a deep learning technique that uses pre-trained models to quickly and accurately diagnose middle ear infections. The method involves fine-tuning pre-trained models on images of the middle ear to detect signs of Otitis Media. This approach can significantly reduce the time and error associated with manual inspections and improve the accuracy of diagnosis, making it a valuable tool for medical professionals.
ResearchGate Technical Report: https://www.researchgate.net/publication/375893659_Otitis_Media_Detection_Using_Deep_Learning
## Run Locally
Clone the project
```bash
git clone https://github.com/bhimrazy/Otitis-Media-Detection-Using-Deep-Transfer-Learning
```
### For frontend
```bash
# Go to the project directory
$ cd frontend
# Install dependencies
$ npm install
# copy env file
cp .env.example .env.local
# Start the server
$ npm run dev
```
### For Backend
```bash
# Go to the project directory
$ cd backend
# create env
$ python -m venv venv
$ source venv/bin/activate
# Install dependencies
$ pip install -r requirements.txt
# copy env file
cp .env.example .env
# Start the server
$ python manage.py serve
```
## Deployment
To deploy this project merge your changes to the main branch.
#### Deployed URLS:
- Frontend : https://otitis-media-detection.vercel.app
- Backend : https://ear-care-iq.up.railway.app
#### Preview
#### System Architecture
#### Some Examples
## Tech Stack
**Client:** NextJs, TailwindCSS
**Server:** Python, FastAPI, PyTorch, ONNX
## Authors
- [Bhimraj Yadav](https://www.github.com/bhimrazy)