https://github.com/vijay-varadarajan/heart-failure-predictor

My first ML project that predicts the risk of heart failure of a person, given his/her medical data, with reasonable accuracy
https://github.com/vijay-varadarajan/heart-failure-predictor

data-science healthcare machine-learning prediction-model python streamlit

Last synced: about 6 hours ago
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My first ML project that predicts the risk of heart failure of a person, given his/her medical data, with reasonable accuracy

• Host: GitHub
• URL: https://github.com/vijay-varadarajan/heart-failure-predictor
• Owner: vijay-varadarajan
• Created: 2023-04-28T07:54:49.000Z (almost 2 years ago)
• Default Branch: master
• Last Pushed: 2024-06-28T11:35:28.000Z (8 months ago)
• Last Synced: 2024-12-15T13:15:59.746Z (about 2 months ago)
• Topics: data-science, healthcare, machine-learning, prediction-model, python, streamlit
• Language: Jupyter Notebook
• Homepage:
• Size: 86.9 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Heart failure risk predictor

### By **Vijay Varadarajan** (22BCB0134)

### Member of IET-VIT

**Streamlit app link**: [Heart failure risk predictor](https://heart-failure-risk-predictor.streamlit.app/)

**Google Colab link**: [Heart-failure-risk-predictor-Colab](https://colab.research.google.com/drive/1IEDbEVnk3WdUmneSHmOp4wH-digWnnY1).


(Download the dataset and upload it to the above google colab before running the program)



**Github link**: [Heart-failure-risk-predictor-Github](https://github.com/vijay-varadarajan/Heart-failure-predictor).

This is a machine learning model that can predict if a person is in a risk of heart failure or not based on the medical data of that person. This is a binary classification model built using the linear kernel in the SVC of Support Vector Machine (SVM). My choice for this model is based on the fact that the dataset used is relatively small but has a lot of feature sets to be processed and this model works well with higher dimensional data. This model has been trained on the recorded data from about 900 people and predicts results with 86% accuracy. 

The dataset for this project was obtained from [heart_data](https://www.kaggle.com/datasets/fedesoriano/heart-failure-prediction?select=heart.csv).




P.S. This is my first machine learning model using numpy, pandas and sklearn. Looking forward to learning more and developing advanced machine learning models in the future.