Diabetes is among critical diseases and lots of people are suffering from this disease. Age, obesity, lack of exercise, hereditary diabetes, living style, bad diet, high blood pressure, etc. can cause Diabetes. People having diabetes have high risk of diseases like heart disease, kidney disease, stroke, eye problem, nerve damage, etc.
Deep learning with neural networks is used to predict the probability of having diabetes in the future.
Based on the feature importance:
- Glucose is the most important factor in determining the onset of diabetes followed by BMI and Age.
- Other factors such as Diabetes Pedigree Function, Pregnancies, Blood Pressure, Skin Thickness and Insulin also contributes to the prediction.
- HTML
- CSS
- Bootstrap
- Flask
- Keras
- Tensorflow
- Deep Learning
- Set up a virtual environment to use for our application.
conda create -n myenv python=3.8- You then need to activate the environment created.
conda activate myenv- Install required libraries:
pip install flask
pip install keras
pip install tensorflow- Create a new working directory for the project
mkdir new-ws- Cd to the workspace and clone the git repo.
cd new-ws
git clone [URL]- Run the app in local environment using python
python app.py- Head over to http://127.0.0.1:5000/ to check the web-app.
- Read Community Guidelines for all kinds of ways to contribute to and interact with the project, including how to submit bug reports and code to Diabetx.
- Submit a proposed code update through a pull request to the
masterbranch. - Talk to us before making larger changes to avoid duplicate efforts. This not only helps everyone know what is going on, it also helps save time and effort if we decide some changes are needed.
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