metadata
tags:
- heart disease prediction
- machine learning
- healthcare
license: mit
library: scikit-learn
dataset: https://www.kaggle.com/datasets/johnsmith88/heart-disease-dataset
Heart Disease Prediction Model 🫀
📌 Model Overview
This model uses Logistic Regression to predict the risk of heart disease based on various health-related features.
📊 Training Data
The model was trained on a dataset containing patient health attributes, including:
- Age
- Cholesterol Level
- Blood Pressure
- Body Mass Index (BMI)
🚀 How to Use the Model
You can download and use the model in Python as follows:
from huggingface_hub import hf_hub_download
import joblib
# Download the model
model_path = hf_hub_download(repo_id="Sarah0022/heart-disease-model", filename="heart_disease_model.pkl")
# Load the model using joblib
model = joblib.load(model_path)