Two Disease Prediction Model

About

This web application was fully developed in Python using Machine Learning libraries and environment. The model was deployed on streamlit cloud server. It predicts the diseases trained on large datasets. The datasets which were used to train the model are mentioned below.

• Diabetes
• Heart Disease

Models with their Accuracy of Prediction

Disease	Model Type	Accuracy
Diabetes	Machine Learning Model	98.53%
Heart Disease	Machine Learning Model	98.41%

NOTE

-> You can access the model at: http://localhost:8501/#diabetes-prediction-using-ml
-> Python version 3.8.19 was used for the whole project.

important steps to run the model in your system

1. download the repository
2. open the command prompt in the downloaded folder
3. setup a virtual environment in the any of the code editor (i.e., VS code, Jupyter Notebook).

mkvvirtualenv environment_name

4. Install all the necessary packages and libraries in already setup virtual environment.

pip install -r requirement.txt

5. Create web app on streamlit cloud server and run it.

python biDiseasePred_public.py

Source of datasets

All the datasets taken into use are from kaggle

• Diabetes Dataset
• Heart Disease Dataset

Seperate links for the python notebooks used to create and train the model

• Diabetes Notebook file
• Heart Disease Notebook file

Contribution

Contributions to improve and enhance the model or add new features to make the mode more efficient are most welcome! kindly fork the repository, create a new branch, and submit a pull request with your changes. It'll be collaborating with y'all. Thanks