This webapp was developed using Flask Web Framework and was deployed on Heroku server. The models used to predict the diseases were trained on large Datasets. All the links for datasets and the python notebooks used for model creation are mentioned below in this readme. The webapp can predict following Diseases:
- Diabetes
- Breast Cancer
- Heart Disease
- Kidney Disease
- Liver Disease
- Malaria
- Pneumonia
| Disease | Type of Model | Accuracy |
|---|---|---|
| Diabetes | Machine Learning Model | 98.25% |
| Breast Cancer | Machine Learning Model | 98.25% |
| Heart Disease | Machine Learning Model | 85.25% |
| Kidney Disease | Machine Learning Model | 99% |
| Liver Disease | Machine Learning Model | 78% |
| Malaria | Deep Learning Model(CNN) | 96% |
| Pneumonia | Deep Learning Model(CNN) | 95% |
==> You can access the website live at: https://kvg-disease-predictor.herokuapp.com
==> Python version 3.6.8 was used for the whole project.
==> You can find all the models in models folder.
- Clone or download the repo.
- Open command prompt in the downloaded folder.
- Create a virtual environment
mkvirtualenv environment_name
- Install all the dependencies:
pip install -r requirements.txt
- Run the application
python app.py
All the datasets were used from kaggle.