Stroke Prediction Random Forest Model

This project uses a Random Forest model to predict the risk of strokes based on user input features. The model has been deployed on Hugging Face for seamless integration.

Features

Predicts the likelihood of a stroke based on various health parameters.
Fast and efficient model, hosted on Hugging Face.

Input Features

The model expects the following inputs:

age: Patient's age (numeric)
age_group: Patients age group child(Less than 18 ),Young Adult (18-34 ), Adult (35-59 ), Senior (60 and over )
hypertension: 1 if the patient has hypertension, else 0
heart_disease: 1 if the patient has heart disease, else 0
avg_glucose_level: Average glucose level in the blood
bmi: Body Mass Index
gender: Male/Female/Other
ever_married: Yes/No
work_type: Type of work (e.g., Private, Self-employed, never_worked)
Residence_type: Urban/Rural
smoking_status: Smoking habits (e.g., never smoked, formerly smoked)

Model Deployment

The model has been deployed on the Hugging Face Hub. You can access it via my repo Random Forest Model for Stroke Prediction.

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