https://github.com/manishkumarpatel07/heartattack_risk_prediction
"Heart Attack Risk Prediction" uses machine learning to estimate the likelihood of a heart attack based on user-provided data like physical attributes, symptoms, and medical history. This system enables remote screening, identifying high-risk individuals, and easing medical system burdens by providing early, data-driven health risk assessments.
https://github.com/manishkumarpatel07/heartattack_risk_prediction
boruta knn-algorithm matplotlib numpy pandas python scikit-learn
Last synced: 3 months ago
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"Heart Attack Risk Prediction" uses machine learning to estimate the likelihood of a heart attack based on user-provided data like physical attributes, symptoms, and medical history. This system enables remote screening, identifying high-risk individuals, and easing medical system burdens by providing early, data-driven health risk assessments.
- Host: GitHub
- URL: https://github.com/manishkumarpatel07/heartattack_risk_prediction
- Owner: ManishKumarPatel07
- Created: 2024-12-27T06:26:40.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2025-02-11T12:25:03.000Z (4 months ago)
- Last Synced: 2025-03-20T15:14:03.515Z (3 months ago)
- Topics: boruta, knn-algorithm, matplotlib, numpy, pandas, python, scikit-learn
- Language: Jupyter Notebook
- Homepage:
- Size: 2.32 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Heart Attack Risk Prediction Using ML
The fact that human life is dependent on the proper functioning
of the heart is the driving force behind this research. The heart
is a crucial part of our bodies, and heart disease has become the
leading cause of death globally. With the increase in number of
deaths among people due to heart diseases, it becomes an issue to
be addressed.
This application takes age, BMI, Systolic BP, Diastolic BP, heart
rate and blood glucose levels as input to give the risk in percentage
associated with having a heart attack in a patient in 10 years time.
## Installation
- Check is python is installed in your system by typing python --version in your command prompt. If not then install python on your system by downloading the setup from the python website [here](https://www.python.org/downloads/).
- Clone the project (or download the folder to your local)
```
git clone https://github.com/ManishKumarPatel07/Heartatack_Risk_Prediction.git
```
- Go to project directory
```
cd project
```
- Install Dependencies
```
pip install numpy pandas matplotlib seaborn scikit-learn boruta statsmodels imbalanced-learn
```
## Run Locally
To run this project, open the code file in vs code studio and then tap on the run all option.
To get the risk associated with heart attack, input the values of age, BMI, Systolic BP, Diastolic BP, heart rate and blood glucose levels and then run the corresponding cell.
## Tech Stack
**Language:** Python
**Libraries:** numpy, pandas, matplotlib, scikit-learn, boruta, imbalanced-learn
## Machine Learning Model Used
K Nearest Neighbor Algorithm
## Authors
- Manish Kumar Patel